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manager ai llmops forward deployed engineer

Andersen

<div>Application Notice:
<div>
We encourage you to apply thoughtfully by selecting one position that best matches your qualifications and interests. You may submit up to two active applications at a time. Please consider your location choice carefully&mdash;we recommend applying where you envision building your future.</div>
The Firm:
<div><b>
A New Era of AI-Driven, Multidimensional Consulting</b></div><div></div><div><br>
Today&rsquo;s businesses face complex global challenges that demand more than conventional consulting services. Andersen Consulting offers a seamless, multidimensional approach that combines expertise in business transformation, artificial intelligence, cybersecurity, sustainability, and digital strategy with Andersen Global&rsquo;s established tax and legal capabilities. This integration of emerging technologies positions Andersen Consulting as the partner of choice in the $1 trillion consulting industry.</div>
The Role:
<p>
At Andersen Consulting, AI/LLMOps FDEs own the technical delivery of production AI systems end-to-end and sit across the table from engineering teams at global enterprises. The practice is early. The engineers who join now will define its architecture, its standards, and what world-class AI delivery looks like for clients who trust us with their most consequential systems.</p><p>
Enterprise AI programs follow a predictable arc: a successful POC, a budget approval, and then months of stalled production work before the initiative quietly dies. The gap between a notebook that impresses stakeholders and a system that runs the business under real enterprise load is an engineering problem. Its name is LLMOps.</p><p>
LLMs have been serious enterprise tools for roughly three years. We are not looking for someone who has mastered a stable field. We are looking for someone who has been in the room while the field was being invented: someone who built RAG pipelines that broke in production, debugged agent loops that silently degraded after staging, and designed eval suites from scratch because nothing off the shelf measured what actually mattered.</p><p><b>
What You'll Do</b></p><p>
Day-to-day, you embed directly with client teams and own a defined technical workstream from design through production:</p><ul><li>
Design and deploy RAG pipelines using pgvector, Pinecone, Qdrant, or Weaviate, with deliberate chunking strategies, hybrid search, and re-ranking layers.</li><li>
Build multi-step agent workflows using LangChain, LangGraph, LlamaIndex, or the Anthropic Claude SDK, with tool use, structured outputs, and memory.</li><li>
Implement guardrails at the correct system boundary: output schema enforcement, PII detection, content filtering, and agent behavior constraints calibrated for each client's regulatory context.</li><li>
Design eval suites in using off-the-shelf tools or custom Python harnesses that measure retrieval quality, answer faithfulness, hallucination rates, and latency under load.</li><li>
Instrument observability from day one: LLM call latency, retrieval quality metrics, agent decision traces, cost per query.</li><li>
Write production Python: typed, tested, linted, and deployable by another engineer.</li><li>
Deploy and serve models on AWS (Bedrock, SageMaker, EKS), Azure (Azure OpenAI Service, AKS), or GCP (Vertex AI, GKE) under latency-sensitive enterprise conditions.</li><li>
Treat prompt and context engineering as an engineering discipline: versioned system prompts, few-shot libraries, chain-of-thought elicitation, and context window budgeting, all of it tracked, tested, and iterated rather than adjusted informally.</li><li>
Build and deploy MCP servers to expose enterprise data sources, internal APIs, and tools to LLM agents in a standardized, auditable way.</li><li>
Contribute reusable accelerators, reference architectures, and internal tooling during bench time. Every asset you build should make the next engagement start faster</li><li>
Travel is a real part of this role. Client work regularly requires on-site presence during discovery, architecture reviews, and go-live.
</li></ul><p><b>What You'll Build</b></p><ul><li>
Production RAG pipelines with hybrid search, re-ranking, and query-time monitoring, designed to hold up under real query distributions and corpus drift, not just benchmark datasets.</li><li>
Multi-step agent orchestration systems with tool use, memory, and structured output validation, built to be reliable at enterprise load, not just demonstrable in a demo environment.</li><li>
Eval frameworks designed from scratch to measure what the client's system actually needs to get right: faithfulness, groundedness, latency percentiles, and failure mode frequency.</li><li>
Guardrail infrastructure positioned correctly in the call stack: input validation, output schema enforcement, and behavioral constraints for the specific regulatory context of each engagement.</li><li>
Observability stacks instrumented at the LLM call, retrieval, and agent decision layer, giving clients operational visibility instead of log files they can't act on.</li><li>
MCP servers exposing internal enterprise systems (databases, document stores, internal APIs) to LLM agents through a standardized, auditable interface.</li><li>
CI/CD pipelines for LLM systems with automated eval runs on prompt changes, model version regression testing, and deployment gating before anything reaches production.</li></ul>
The Requirements:
<ul><li>7+ years of total experience in data engineering, MLOps, software engineering, or closely adjacent infrastructure roles, with evidence of end-to-end ownership: architecture through production, including the post-launch work.</li><li>
2&ndash;3 years of LLM-specific engineering experience is credible at this level. That is the ceiling given when the field started, not a floor. What distinguishes senior candidates is judgment: knowing when an agent architecture is the right tool, how to design for observability before it is needed, and how to have the hard conversation when a POC is not production-ready.</li><li>
Production Python. Typed, tested, and structured for multi-engineer deployment. We will ask about your testing practices and code review standards.</li><li>
At least one production LLM system shipped: a RAG pipeline, agent workflow, or LLM-powered application that handled real enterprise load, not just internal demos. The key question is what broke after launch and what you did about it.</li><li>
Hands-on vector retrieval experience with pgvector, Pinecone, Qdrant, Weaviate, or Chroma, including hybrid search design, embedding quality diagnosis, and re-ranking strategy selection, not just initial setup.</li><li>
Working knowledge of at least one agentic SDK (Anthropic Claude SDK, LangChain, LangGraph, LlamaIndex, or OpenAI SDK) in a non-trivial use case involving tool use, memory, or structured output handling.</li><li>
Cloud AI infrastructure depth in at least one of AWS (Bedrock, SageMaker, EKS), Azure (Azure OpenAI Service, AKS), or GCP (Vertex AI, GKE).</li><li>
LLM observability experience: you have instrumented a system before, not just read the documentation.</li><li>
Enough communication clarity to explain an architecture decision to an engineering team and a business stakeholder in the same meeting. These are client-facing roles.</li><li>
Travel up to 50%</li></ul><p><b>
Preferred Qualifications</b></p><ul><li>
Model serving experience in latency-constrained environments.</li><li>
Guardrail implementation experience in regulated data contexts: PHI, PII, or MNPI.</li><li>
RAGAS or custom eval harness experience.</li><li>
MCP server development. Still rare enough that hands-on experience is high signal.</li><li>
Palantir Foundry or AIP experience, a meaningful differentiator as Andersen's Palantir practice scales alongside the LLMOps practice.</li><li>
Prior client-facing or consulting experience. FDEs who understand stakeholder management and expectation-setting ramp faster and derisk engagements earlier.</li><li>
Domain exposure in financial services (insurance, reinsurance, credit), healthcare, supply chain, or manufacturing.</li></ul><div><b>
Compensation and Benefits</b></div><div><br>
Our firm offers a competitive base salary and comprehensive benefits package designed to support the well-being, growth, and long-term success of our people. We are committed to recognizing individual contributions and providing resources that enable our employees to thrive both personally and professionally.</div><div></div><div><b><br>
Salary Range</b>: For individuals hired to work in New York, the expected salary range for this role is $195,875 - 266,171. Actual compensation will be determined based on the candidate&rsquo;s qualifications, experience, and skill set.</div><div></div><div><b><br>
Benefits</b>: Employees (and their families) are eligible for medical, dental, vision, and basic life insurance coverage. Employees may enroll in the firm&rsquo;s 401(k) plan upon hire. We offer 200 hours of paid time off annually, along with twelve paid holidays each calendar year. For a full listing of benefit offerings, please visit https://www.andersen.com/careers.</div><div><br>
</div><div><i>Applicants must be currently authorized to work in the United States on a full-time basis upon hire. Andersen will not consider candidates for this position who require sponsorship for employment visa status now or in the future (e.g., H-1B status).</i></div><div><i><br>
Andersen Tax is an equal opportunity employer committed to fostering an inclusive workplace. We evaluate all applicants and employees without regard to race, color, religion, national origin, ancestry, sex (including pregnancy, childbirth, and related medical conditions), sexual orientation, gender identity or expression, age, disability, genetic information, marital status, military or veteran status, or any other characteristic protected under applicable federal, state, or local law. All qualified applicants, including those with criminal histories, will be considered in a manner consistent with applicable law. We provide reasonable accommodations to qualified individuals with disabilities as required by law.</i></div><div></div><div><b><br>
ANDERSEN TAX LLC NOTICE FOR JOB</b> APPLICANTS</div></div>

Manager - AI/LLMOps Forward Deployed Engineer

Edra

<div>
 <strong>
  About Edra
  <br/>
  <br/>
 </strong>
 Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations.
 <br/>
 <br/>
 We're a Series A startup, backed by Sequoia and other leading VC firms, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build.
 <br/>
 <br/>
 <strong>
  The Role
  <br/>
  <br/>
 </strong>
 We're looking for Full Stack Engineers who care deeply about the craft of building software: strong typing, thoughtful API design, robust data modeling, and interfaces that are a pleasure for both users and other engineers to work with. You won't be building AI models&ndash;you'll be building everything around them: the platform, workflows, user-facing experiences, integrations, and observability that make our AI useful in the real world. As an early engineer at Edra, you'll shape not just the product but the engineering culture, tooling choices, and technical foundations the company is built on.
 <br/>
 <br/>
 We work deliberately and deeply. There's no separation between "building it" and "shipping it"--you'll go from whiteboard to production and own the outcome. We'd rather build something thoughtfully than ship something fragile, and we treat velocity and quality as complementary, not competing.
 <br/>
 <br/>
 <strong>
  What You'll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design and build platform systems in Python (FastAPI)--from API contracts to database schema and infrastructure&ndash;and high-quality user-facing experiences in TypeScript and React, with an emphasis on clean component design, strong typing, and maintainable frontends
  </li>
  <li>
   Build shared TypeScript and Python libraries, component systems, and internal tooling that make the rest of the engineering team more productive. Define and enforce patterns, shared types, and contracts across the frontend and API boundary
  </li>
  <li>
   Own your work fully: gather context, manage dependencies, and drive tasks to completion without a product manager handing you tickets. You might design a schema in the morning, build a React component in the afternoon, and debug a deployment issue before end of day
  </li>
  <li>
   Contribute to the direction and design of our product. Work closely with design, reason clearly about interface decisions, and participate in weekly product meetings to understand how customers and forward-deployed engineers use what you build
  </li>
  <li>
   Build and maintain connectors, integrations, and data pipelines that connect our platform to external systems
  </li>
  <li>
   Have direct influence on technical direction; choose tools, set patterns, and establish conventions the team will build on for years. Collaborate daily with a small, high-caliber team of engineers and AI specialists
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We&rsquo;re Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   3+ years of experience in software engineering (but a computer science degree is not necessarily required)
  </li>
  <li>
   A love of writing Python and TypeScript to a genuinely high standard&ndash;well-modeled, well-typed, and well-documented. Strong typing feels like a superpower, not a chore
  </li>
  <li>
   You light up when designing a clean database schema and take real pride in getting data models right
  </li>
  <li>
   You have good visual and interaction judgment, even if you're not a designer by title
  </li>
  <li>
   You've built libraries, SDKs, or internal tooling that made other developers' lives easier (and you&rsquo;ve enjoyed it)
  </li>
  <li>
   You're at your best when you own a problem end to end&ndash;comfortable with ambiguity and energized by turning a vague problem into a well-scoped solution
  </li>
  <li>
   You're drawn to building foundational systems from scratch&ndash;greenfield work where your decisions compound over time excites you
   <br/>
   <br/>
  </li>
 </ul>
 Don't meet all of the above? We'd still love to hear from you. We're looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets. If your primary interest is building agentic systems, working with LLMs, or doing applied ML, check out our AI Engineering role&ndash;it might be a better fit.
 <br/>
 <br/>
 <strong>
  Learn More About Edra
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Watch our Series A announcement video
  </li>
  <li>
   Read our blog post from our launch
  </li>
  <li>
   Learn more about what we're building
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  A Few Details
  <br/>
  <br/>
 </strong>
 Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
 <br/>
 <br/>
 Compensation Range: $180K - $250K
 <br/>
 <br/>
</div>


Software Engineer - Full Stack (New York)

COMPLEX

<div><div><b>Company And Culture</b></div>
<div></div>
<div>Complex is the definitive platform for global youth culture and music lifestyle, seamlessly integrating cutting-edge content, commerce and live experiences with unparalleled scale. Through innovative content, Complex tells stories of music, streetwear and style, sports, art and beyond. Its content engages in a dynamic conversation with the audience, reflecting and shaping the zeitgeist of convergence culture. A powerful media juggernaut paired with a curated marketplace, Complex is redefining the way fans interact with their favorite brands and artists and reshaping the future of digital culture and commerce.</div>
<div></div>
<div><b>Why We're Hiring
</b></div>
<div></div><div>Complex operates at the intersection of content, commerce, and culture&mdash;powering media, live experiences, marketplace, and audience engagement across sneakers, music, sports, and streetwear. This ecosystem generates a high volume of workflows, audience intelligence, and creative output. Much of that operational value, however, remains fragmented across SaaS platforms, manual processes, and institutional knowledge. We are building the next layer of infrastructure to change that.
</div>
<div></div><div>The AI Orchestra Director: Agentic Infrastructure Engineer will embed directly within our technology organization, ensuring that every architectural decision drives measurable business outcomes. The role bridges system design, implementation, and operational impact. Complex is seeking an AI Orchestra Director&mdash;a hands-on technical architect and builder responsible for designing, deploying, and operationalizing our agentic AI infrastructure. This is not an advisory position. It is an execution-driven engineering mandate to build a parallel infrastructure layer that enables AI agents to:</div>
<ul><li>Automate core workflows</li></ul>
<ul><li>Replace high-cost SaaS platforms with owned solutions</li></ul>
<ul><li>Modernize data access and experimentation</li></ul>
<ul><li>Generate proprietary, reusable intellectual property</li></ul>
<ul><li>All while the business continues to operate without disruption</li></ul>
<div></div>
<div><b>Work Schedule:</b></div>
<div>Possible freelance to hire, 4-6 month project Monday - Friday</div>
<h3 class="jobSectionHeader"><b>What You'll Do</b></h3><ul>
<li><b>Top Three Strategic Priorities:</b></li>
<li>1. Architect and Deploy the Agentic Infrastructure Layer</li>
<li>Design and implement a scalable runtime environment purpose-built for a media and commerce organization, including:</li>
<li>Agent orchestration and task routing</li>
<li>Quality gates and human-in-the-loop checkpoints</li>
<li>Logging, observability, and convergence tracking</li>
<li>CI/CD and deployment pipelines</li>
<li>On-premise or hybrid environment architecture</li>
<li>This foundation must be secure, extensible, and maintainable by the existing engineering team</li>
</ul>
<div></div><ul><li>2. Lead the Tool Replacement Program</li>
<li>Audit current SaaS licenses and identify high-cost, high-leverage replacement opportunities (e.g., CRM, analytics, workflow tools)</li>
<li>Using agentic development practices:</li>
<li>Build internal tools with AI agents writing and testing code</li>
<li>Maintain human review at critical checkpoints</li>
<li>Deliver measurable license cost reductions</li>
<li>Demonstrate infrastructure ROI within the engagement period</li>
<li>The objective: prove the system&rsquo;s value by using agents to build the tools themselves</li>
</ul>
<div></div><ul><li>3. Codify Operational Workflows into a Reusable Skills Library</li>
<li>Partner across departments to:</li>
<li>Identify and document high-impact operational workflows</li>
<li>Encode them into version-controlled, reusable agent &ldquo;skills&rdquo;</li>
<li>Transform tribal knowledge into durable company-owned IP</li>
<li>The result: a scalable library of automated capabilities that can operate independently of the engagement</li>
</ul>
<div></div><ul><li><b>Key Responsibilities:</b></li>
<li>Architect and deploy the agentic infrastructure layer in collaboration with executive leadership and the Platform Studio engineering team</li>
<li>Design a modern, growth-oriented data access layer built on existing Snowflake infrastructure and related data sources</li>
<li>Enable agent-native querying, rapid experimentation, and insight generation</li>
<li>Evaluate and integrate open-source orchestration tools to maintain vendor-agnostic flexibility</li>
<li>Implement test-driven development enforcement, intelligent retry logic, and convergence tracking</li>
<li>Establish governance frameworks with human-in-the-loop checkpoints for production deployment and auditability</li>
<li>Embed seamlessly with existing engineering teams&mdash;building trust, not parallel power structures</li>
<li>Develop documentation, training protocols, and knowledge-transfer systems to ensure long-term sustainability</li>
<li>Partner with the COO and department leaders to prioritize automation initiatives that simultaneously reduce cost and increase velocity</li>
<li>Foster a culture shift toward agentic development as a core capability within the organization</li>
</ul><h3 class="jobSectionHeader"><b>Who You Are</b></h3><ul>
<li>Proven experience building and deploying AI agent infrastructure in production environments</li>
<li>Deep proficiency across LLM orchestration frameworks, retrieval-augmented generation (RAG), prompt engineering, and agentic coding workflows</li>
<li>Strong systems architecture background with infrastructure designed for long-term maintainability</li>
<li>Experience with data engineering and analytics infrastructure (Snowflake and API-based systems preferred)</li>
<li>Comfort evaluating and integrating open-source tooling within a multi-model ecosystem (e.g., Claude, Codex, Gemini, open-source models)</li>
<li>Git-native workflow mindset (branches, PRs, CI/CD, TDD)</li>
<li>Exceptional ability to translate complex architecture into business-aligned outcomes</li>
<li>Experience embedding within existing teams and leaving them stronger than you found them</li>
<li>Media, entertainment, or commerce industry experience preferred but not required</li>
<li>Comfortable with whiteboarding systems with executive leadership</li>
<li>Creating shipping production-ready pipelines</li>
<li>Reviewing agent-generated code</li>
<li>Ability to train teams to extend what you&rsquo;ve built</li>
</ul>
<div></div><ul><li><b>Success Metrics (By the end of the 12 week engagement, you will have delivered):</b></li>
<li>A working agent runtime environment with orchestration, logging, quality gates, and CI/CD pipelines</li>
<li>At least two deployed internal SaaS replacements with documented cost savings</li>
<li>A versioned skills library containing a minimum of ten codified operational workflows</li>
<li>A defined and partially implemented data access layer serving both human users and AI agents</li>
<li>Complete knowledge transfer to the existing engineering team</li>
<li>Seamless organizational integration with no structural friction</li>
</ul>
<div></div><ul><li><b>What Success Looks Like:</b></li>
<li>Success is not measured solely by architectural elegance &ndash; It is measured by operational independence</li>
<li>Workflows that execute autonomously</li>
<li>Tools built internally rather than rented</li>
<li>Data systems that surface insights proactively</li>
<li>An engineering organization fluent in agentic development</li>
</ul><div>The Pay Range, which consists of salary and commission, for this position is listed. Actual pay will vary based on factors including, but not limited to location, experience, and performance. The range listed is just one component of Complex Total Rewards offerings for employees.</div><div>
We're an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status.</div>
<div></div>
<div><i>The above statements cover what are generally believed to be principal and essential functions of the job. Specific circumstances may allow or require some incumbents assigned to the job to perform a different combination of duties.</i></div>
<div></div>
<div><i>Complex participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.</i></div>
<div></div>
<div><i>Candidates must be legally authorized to work in the U.S. without the need for visa sponsorship.</i></div></div>

Director, Agentic AI Infrastructure & Orchestration Engineer

<div>
 <p>
  <strong>
   Role: Senior Data Analytics Engineer with AI Initiatives (Must)
  </strong>
 </p>
 <p>
  <strong>
   Location: New York/ Remote
  </strong>
 </p>
 <p>
  <strong>
   Experience: 5 - 10 years
  </strong>
 </p>
 <p>
  <strong>
   Duration: Full time
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Job Description:
  </strong>
 </p>
 <p>
  We are looking for a Lead Engineer to build and maintain scalable data pipelines and data platforms that support analytics, business Intelligence, reporting, and AI initiatives. In this role, you will work closely with data architects, analysts, and business stakeholders to develop reliable data solutions and ensure high-quality data is available across the organization.
 </p>
 <p>
  This is a
  <strong>
   hands-on engineering role
  </strong>
  focused on designing efficient data pipelines, improving data infrastructure, and enabling teams to leverage data effectively.
 </p>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Responsibilities
  </strong>
 </p>
 <ul>
  <li>
   Design, build, and maintain scalable
   <strong>
    data pipelines and ETL/ELT workflows
   </strong>
   to ingest and transform data from multiple sources
  </li>
  <li>
   Develop and optimize
   <strong>
    batch and near real-time data processing pipelines
   </strong>
   for analytics and reporting
  </li>
  <li>
   Build and maintain
   <strong>
    data warehouse and data lake structures
   </strong>
   to support business intelligence and analytics use cases
  </li>
  <li>
   Implement and maintain
   <strong>
    data models
   </strong>
   that support efficient querying and reporting
  </li>
  <li>
   Improve performance and scalability of data systems through
   <strong>
    query optimization, indexing, and partitioning strategies
   </strong>
  </li>
  <li>
   Implement
   <strong>
    data quality checks, monitoring, and logging
   </strong>
   to ensure reliability of data pipelines
  </li>
  <li>
   Exposure to
   <strong>
    AI initiatives
   </strong>
   and experience
   <strong>
    building data pipelines
   </strong>
   supporting
   <strong>
    AI workflows
   </strong>
  </li>
  <li>
   Work with data architects and engineering teams to implement
   <strong>
    scalable data platform designs
   </strong>
  </li>
  <li>
   Collaborate with analysts, BI developers, and business stakeholders to deliver data solutions that support business needs
  </li>
  <li>
   Maintain documentation for data pipelines, data models, and data workflows
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Requirements
  </strong>
 </p>
 <ul>
  <li>
   <strong>
    5 - 10 years of experience
   </strong>
   in Data Engineering and GenAI and Data Scientist and AI Engineer
  </li>
  <li>
   Strong experience with
   <strong>
    SQL and Python
   </strong>
   for data processing and transformation
  </li>
  <li>
   Experience building and maintaining
   <strong>
    ETL/ELT pipelines
   </strong>
  </li>
  <li>
   Solid understanding of
   <strong>
    data warehousing concepts and dimensional data modeling
   </strong>
  </li>
  <li>
   Experience working with
   <strong>
    cloud data platforms or modern data infrastructure
   </strong>
  </li>
  <li>
   Familiarity with
   <strong>
    workflow orchestration tools
   </strong>
   such as
   <strong>
    Airflow
   </strong>
   or similar
  </li>
  <li>
   Understanding of
   <strong>
    API-based data ingestion and data integration patterns
   </strong>
  </li>
  <li>
   Strong problem-solving and collaboration skills
  </li>
 </ul>
 <p>
  <br/>
 </p>
 <p>
  <strong>
   Education
  </strong>
 </p>
 <p>
  Bachelor's or master's degree in computer science
  <strong>
   , Engineering, Information Systems, or a related field
  </strong>
  , or equivalent practical experience.
 </p>
</div>


AI Data Engineer

Optum

<div><p>Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start <b>Caring. Connecting. Growing together.</b></p><p></p><p><br>
Optum AI is UnitedHealth Group's enterprise AI team. We are AI/ML scientists and engineers with deep expertise in AI/ML engineering for health care. We develop AI/ML solutions for the highest impact opportunities across UnitedHealth Group businesses including UnitedHealthcare, Optum Financial, Optum Health, Optum Insight, and Optum Rx. In addition to transforming the health care journey through responsible AI/ML innovation, our charter also includes developing and supporting an enterprise AI/ML development platform.</p><p></p><p><b><br>
Optum AI team members:</b></p><ul><li>
Have impact at scale: We have the data and resources to make an impact at scale. When our solutions are deployed, they have the potential to make health care system work better for everyone</li><li>
Do ground-breaking work: Many of our current projects involve cutting edge ML, NLP and LLM techniques. Generative AI methods for working with structured and unstructured health care data are continuously being developed and improved. We are working in one of the most important frontiers of AI/ML research and development</li><li>
Partner with world-class experts on innovative solutions: Our team members are developing novel AI/ML solutions to business challenges. In some cases, this includes the opportunity to file patents and publish papers about the methods we develop. We also collaborate with AI/ML researchers at some of the world's top universities</li></ul><p></p><p><br>
You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.</p><p></p><p><b><br>
Primary Responsibilities:</b></p><ul><li>
Build and test deep learning and traditional ML models in distributed computing environments</li><li>
Develop robust machine learning pipelines and ML Ops procedures to support production processes</li><li>
Process and transform source data to be used in machine learning pipelines, leveraging distributed computing environments and parallel processing approaches</li><li>
Develop robust modules for evaluation and drift detection</li><li>
Design and plan experiments, conduct statistical analysis and create data visualizations</li><li>
Communicate findings with business stakeholders and collaborate to develop solutions that meet customer needs</li><li>
Develop code and model documentation and assist with model governance approvals</li></ul><p></p><p><br>
You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.</p><p><b>
Required Qualifications:</b></p><ul><li>
BS in computer science or a related quantitative field</li><li>
2+ years of AI/ML experience</li><li>
2+ years of experience with Python, classical ML methods and deep learning, including deep learning frameworks such as PyTorch or Tensorflow</li><li>
Experience with LLM frameworks and/or NLP approaches such as text embedding and text classification</li></ul><p></p><p><b><br>
Preferred Qualifications:</b></p><ul><li>
MS or PhD in computer science or related quantitative field</li><li>
Experience with distributed computing approaches such as Spark</li><li>
Experience with Snowflake and other relational databases</li><li>
Experience building Python libraries</li><li>
Experience working on collaborative software projects using GitHub</li><li>
Experience developing simple UIs for POCs demonstrating AI/ML models</li><li>
Proven solid technical communication skills</li></ul><p></p><ul><li><br>
All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy</li></ul><p></p><p><br>
Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 to $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.</p><p></p><p><b><br>
Application Deadline: </b>This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.</p><p></p><p><i><br>
At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.</i></p><p></p><p><i><br>
UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.</i></p><p></p><p><i><br>
UnitedHealth Group is a drug free workplace. Candidates are required to pass a drug test before beginning employment.</i></p></div>

Senior AI/ML Scientist - Remote

Galaxy

<div>
 <strong>
  Who We Are
  <br/>
  <br/>
 </strong>
 Galaxy is a global leader in digital assets and data center infrastructure, delivering solutions that accelerate progress in finance and artificial intelligence. We believe that blockchain and digital asset innovation will transform how value moves through the world &ndash; and we&rsquo;re building the products and services to make that future a reality.
 <br/>
 <br/>
 Our institutional digital assets platform spans trading, investment banking, asset management, staking, self-custody, and tokenization technology. We also invest in and operate cutting-edge data center infrastructure to power AI and high-performance computing, addressing the growing demand for scalable energy and compute in the U.S.
 <br/>
 <br/>
 We work at the intersection of finance and technology, helping institutions, startups, and developers navigate a digitally native economy. Led by CEO and Founder Michael Novogratz, our team blends deep crypto expertise with institutional experience and a shared commitment to shaping the future of Web3 and AI.
 <br/>
 <br/>
 Galaxy is headquartered in New York City, with offices across North America, Europe, the Middle East, and Asia.
 <br/>
 <br/>
 To learn more about our businesses and products, visit www.galaxy.com.
 <br/>
 <br/>
 <strong>
  What We Value
  <br/>
  <br/>
 </strong>
 We are a diverse team of free thinkers, and fast movers united to help investors and creators energize the global economy. We are looking for individuals who thrive in a culture of builders and overachievers and embrace high performance, transparent feedback, and a mission-first approach. Our culture shapes our way of working and gets us where we want to be.
 <br/>
 <br/>
 <ul>
  <li>
   Seek Excellence.
  </li>
  <li>
   Be Selective To Be Effective.
  </li>
  <li>
   Be Highly Aligned, Loosely Coupled.
  </li>
  <li>
   Disagree Transparently.
  </li>
  <li>
   Encourage Independent Decision-Making.
  </li>
  <li>
   Build Dream Teams.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Who You Are
  <br/>
  <br/>
 </strong>
 We are seeking a highly organized, detail-oriented Marketing Manager (Analyst-level) to support cross-functional marketing initiatives across the firm. This role is ideal for someone early in their career who wants exposure to all facets of marketing &mdash; product marketing, content, brand, campaigns, and events&mdash; while building strong execution and analytical foundations. You will act as a force multiplier for the team: ensuring projects move forward, materials are polished, data is accurate, and internal coordination runs smoothly.
 <br/>
 <br/>
 This is a generalist role designed for someone who thrives in fast-paced environments and enjoys both creative and analytical work. You&rsquo;ll gain exposure to institutional crypto markets, cross-functional experience across multiple marketing disciplines, mentorship from senior marketing leadership, and a strong foundation in execution, analytics, and strategic marketing operations.
 <br/>
 <br/>
 <strong>
  What You&rsquo;ll Do
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Support end-to-end execution of marketing initiatives across campaigns, digital channels, product launches, and events.
  </li>
  <li>
   Maintain and update the marketing content calendar, project trackers, and documentation to ensure deadlines and deliverables stay on track.
  </li>
  <li>
   Monitor campaign performance and pull marketing analytics to support reporting and continuous improvement.
  </li>
  <li>
   Create and format marketing materials including newsletters, website content, social posts, graphics, and sales decks.
  </li>
  <li>
   Ensure brand consistency, accuracy, and quality control across all marketing assets.
  </li>
  <li>
   Take structured meeting notes, track action items, and support cross-functional coordination
  </li>
  <li>
   Use AI tools and internal systems to streamline workflows, summarize insights, and improve operational efficiency.
  </li>
  <li>
   Stay informed on industry and competitor trends to support thoughtful marketing execution.
  </li>
  <li>
   Come to the office on a hybrid schedule (4-in/1-remote).
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We&rsquo;re Looking For
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   1&ndash;2+ years of experience in marketing, communications, finance, or a related field
  </li>
  <li>
   Comfortable working in a fast-paced, deadline-driven environment
  </li>
  <li>
   Exceptional attention to detail &mdash; you catch formatting errors others miss
  </li>
  <li>
   Strong organizational &amp; time management skills
  </li>
  <li>
   Clear written and verbal communication
  </li>
  <li>
   Highly reliable and proactive
  </li>
  <li>
   Low ego, high ownership
  </li>
  <li>
   Curious about digital assets and financial markets
  </li>
  <li>
   Motivated to grow into a broader marketing or product marketing role over time
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  What We Offer (US)
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Competitive base salary and discretionary bonus
  </li>
  <li>
   Flexible Time Off (i.e. unlimited paid vacation days)
  </li>
  <li>
   Company paid Holidays (11)
  </li>
  <li>
   Company paid sick leave
  </li>
  <li>
   Company-paid health and protective benefits for employees, partners, and other dependents
  </li>
  <li>
   Competitive family planning benefits for US employees
  </li>
  <li>
   3% 401(k) company contribution
  </li>
  <li>
   Generous paid Parental Leave
  </li>
  <li>
   Free virtual coaching and counseling sessions through Headspace
  </li>
  <li>
   Opportunities to learn about the Crypto industry
  </li>
  <li>
   Free daily snacks in-office
  </li>
  <li>
   Smart, entrepreneurial, and fun colleagues
  </li>
  <li>
   Employee Resource Groups
  </li>
  <li>
   Benefits may vary depending on location.
   <br/>
   <br/>
  </li>
 </ul>
 <em>
  Apply now and join us on our mission to engineer a new economic paradigm.
  <br/>
  <br/>
 </em>
 The base salary ranges included below will be commensurate with candidate experience, expertise and local market. Final offer amounts are determined by multiple factors, including candidate experience and expertise. At Galaxy, we maintain a total compensation philosophy which consists of a competitive base salary, annual bonus, and equity incentives.
 <br/>
 <br/>
 Base Salary Range
 <br/>
 <br/>
 $100,000 - $120,000 USD
 <br/>
 <br/>
 <em>
  Galaxy respects diversity and seeks to provide equal employment opportunities to all employees and job applicants for employment without regard to actual or perceived age, race, color, creed, religion, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression (including transgender status), sexual orientation, marital or partnership or caregiver status, ancestry, national origin, citizenship status, disability, military or veteran status, protected medical condition as defined by applicable state or local law, genetic information or predisposing genetic characteristic, or other characteristic protected by applicable federal, state, or local laws and ordinances.
  <br/>
  <br/>
 </em>
 <em>
  We will endeavor to make a reasonable accommodation to the known limitations of a qualified applicant with a disability unless the accommodation would impose an undue hardship on the operation of our business. If you believe you require such assistance to complete the application process or to participate in an interview, please contact careers@galaxy.com.
 </em>
</div>


Marketing Manager

Locality

<div><p>Locality is seeking a Senior Data Engineer whom will serve as the primary internal owner of our Audience Engine, spanning data ingestion, identity resolution, automation, and AI enablement. This role emphasizes hands on platform stewardship today, with a clear path to supporting future expansion of the HH Identity Graph and applied AI use cases.
</p><ul><li>Establish and own technical management of the Audience Engine, transitioning knowledge from external partners and building a scalable, internally managed data platform</li><li>
Reduce reliance on third-party vendors while maintaining high standards for platform reliability, uptime, and data integrity across all pipelines and integrations</li>
Architect, own, and continuously optimize Databricks Bronze Silver<li> Gold pipelines to support large scale audience ingestion, enrichment, and activation workflows</li><li>
Ensure the platform is scalable and cost efficient through effective pipeline optimization and resource management</li><li>
Proactively monitor, troubleshoot, and resolve ingestion failures, schema drift, and data quality issues across batch and near real time data pipelines</li><li>
Lead identity resolution across datasets including HHID, DSID, MAID, IP, and campaign logs, improving matching logic to strengthen the Household Identity Graph</li><li>
Guarantee accurate and timely audience publication by maintaining robust downstream data delivery processes and SLAs across activation platforms and partners</li><li>
Own and maintain integrations with external data and activation partners (e.g., Experian, FreeWheel, DSPs), ensuring seamless data exchange and operational reliability</li><li>
Partner cross functionally with Product, Analytics, and Ad Operations teams to onboard new data sources and activation endpoints, enabling new use cases and revenue opportunities</li><li>
Support and operationalize applied AI/ML workflows within Databricks, including integration with tools like Akkio, and translate business needs into production-ready data features and datasets</li><li>
Design and implement scalable data models and query-ready datasets that power BI reporting, audience insights, and predictive modeling, ensuring alignment with downstream analytics requirements</li><li>
Enforce data governance, lineage, and documentation standards while ensuring compliance with privacy, consent, and data usage regulations across all audience and identity data systems</li></ul><ul><li>
6+ years of experience as a Data Engineer or Data Platform Engineer, ideally within advertising</li><li>
Strong hands on experience with Databricks, Spark, and modern cloud data platforms</li><li>
Proven experience designing and maintaining multi-layered data architectures (Bronze / Silver / Gold)</li><li>
Deep expertise in SQL and proficiency in Python or another scripting language</li><li>
Experience working with identity graphs, audience data, and complex join logic across large datasets</li><li>
Hands on experience building and managing automated data pipelines and third-party data integrations</li><li>
Familiarity with adtech, martech, or audience activation platforms, including exposure to identity providers such as Experian or similar vendors</li><li>
Practical experience supporting AI/ML workflows or AI-enabled analytics, with an understanding of data quality, schema design, and performance optimization in cloud-scale environments</li></ul><p>
</p><p><i>Compensation for the role includes a competitive base salary in the range from $75-$100/hr (dependent on years of experience, level of education obtained, as well as applicable skillset), and an excellent benefits package (including but not limited to health care benefits, retirement benefits and paid days off).
</i></p><p></p><p><i>At Locality, we believe our biggest asset is our people. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. Locality values and solicits applications from all qualified candidates without regard to actual or perceived race, creed, color, religion, sex, gender, age, physical or mental disability, medical condition, sexual orientation, gender identity and/or expression, alienage or national origin, ancestry, citizenship status, marital status, military or veteran status, genetic information, or any other basis protected by federal, state, or local law.</i></p></div>

Sr. Data Engineer (Contract to Perm)

Explore 433+ Manager ai llmops forward deployed engineer in New York this April. Find roles across top companies and apply now to boost your career.