senior ai engineer

WEX Inc.

<div><p>This is a remote position; however, the candidate must reside within 30 miles of one of the following locations: Portland, ME; Boston, MA; Chicago, IL; Dallas, TX; San Francisco Bay Area, CA; and Seattle/WA.</p><p></p><div><b>
About the Team</b></div><p><b>
We are a fast-growing AI Engineering team, driving WEX's strategic vision to integrate artificial intelligence into the core of our product and business. Our team thrives on collaboration, working directly with stakeholders and domain experts to develop innovative AI platforms and solutions that enhance decision-making and create groundbreaking products that benefit our customers and help them to effectively grow their business. We foster a culture of continuous learning and believe that the best work stems from a shared purpose and an enjoyable, engaging environment.</b></p><p></p><div><b>
How You&rsquo;ll Make an Impact</b></div><p></p><p><b>
You are an experienced technical leader and subject matter expert with a deep passion for AI, Machine Learning, and software engineering. You possess a proven track record of architecting scalable systems and solving complex ambiguity using data-driven tools. You will act as a force multiplier for the team&mdash;setting technical standards, mentoring junior engineers, and partnering with product leadership to turn abstract business goals into production-grade AI solutions.</b></p><div></div><div><b>
Responsibilities</b></div><ul><li><p><b>
Technical Strategy &amp; Architecture:</b><b> Partner with stakeholders to translate complex customer challenges into robust technical designs and AI strategies.</b></p></li><li><p><b>
End-to-End Ownership:</b><b> Architect, build, and deploy high-performance AI/ML platforms and tools, ensuring scalability, reliability, and security.</b></p></li><li><p><b>
Advanced Model Development:</b><b> Lead the development, evaluation, fine-tuning, and monitoring of production-grade AI/ML models (including LLMs and RAG architectures).</b></p></li><li><p><b>
Operational Excellence:</b><b> Design and standardize CI/CD pipelines (GitHub Actions) and Infrastructure as Code (Terraform) to ensure reproducible and automated deployments.</b></p></li><li><p><b>
Reliability &amp; Scale:</b><b> Proactively monitor system health, lead incident response for critical AI systems, and drive architectural refactoring to remove bottlenecks.</b></p></li><li><p><b>
Mentorship:</b><b> Mentor L1/L2 engineers, conduct code reviews, and foster a culture of engineering excellence and best practices.</b></p></li><li><p><b>
Innovation:</b><b> Evaluate emerging AI technologies/vendors and prototype new approaches to keep the organization at the cutting edge of the industry.</b></p></li></ul><div></div><div><b>
Experience You&rsquo;ll Bring</b></div><ul><li><p><b>
5+ years</b><b> of experience as an AI/ML Engineer, Data Scientist, or Software Engineer with a heavy focus on production ML systems.</b></p></li><li><p><b>
Bachelor's degree in Computer Science, Software Engineering, or related field; a Master&rsquo;s or PhD in AI/ML is preferred.</b></p></li><li><p><b>
Production expertise:</b><b> Proven track record of taking AI solutions from concept to high-scale production using Java, C#, GoLang, or Python.</b></p></li><li><p><b>
LLM Proficiency:</b><b> Deep experience with Generative AI, including prompting strategies, RAG (Retrieval-Augmented Generation), fine-tuning, and agentic workflows.</b></p></li><li><p><b>
System Design:</b><b> Strong ability to design distributed systems and microservices architectures for model serving.</b></p></li><li><p><b>
Collaboration:</b><b> Demonstrated ability to lead technical discussions with non-technical stakeholders and drive consensus.</b></p></li><li><p><b>
Experience in the financial or fintech industry is a plus.</b></p></li></ul><div></div><div><b>
Technical Skills</b></div><ul><li><p><b>
Expert proficiency</b><b> in Python (preferred) or other core languages (Java, Go, C#).</b></p></li><li><p><b>
Deep knowledge of modern ML frameworks (PyTorch, TensorFlow, Scikit-learn) and LLM orchestration (LangChain, LlamaIndex, vLLM).</b></p></li><li><p><b>
Advanced understanding of MLOps principles, feature stores, and model monitoring.</b></p></li><li><p><b>
Solid grasp of advanced probability, statistics, and linear algebra.</b></p></li><li><p><b>
Extensive hands-on experience with </b><b>Kubernetes</b><b> (deploying and managing clusters) and Cloud platforms (AWS preferred).</b></p></li><li><p><b>
Strong command of CI/CD methodologies and Infrastructure as Code (Terraform).</b></p></li><li><p><b>
Excellent data engineering skills (SQL, NoSQL, data lakes, and processing pipelines).</b></p></li></ul><div><b>
Key Words</b></div><p><b>
Senior AI Engineer, MLOps, Generative AI, LLM, RAG, Distributed Systems, Software Architecture, Technical Leadership.</b></p><p></p>
The base pay range represents the anticipated low and high end of the pay range for this position. Actual pay rates will vary and will be based on various factors, such as your qualifications, skills, competencies, and proficiency for the role. Base pay is one component of WEX's total compensation package. Most sales positions are eligible for commission under the terms of an applicable plan. Non-sales roles are typically eligible for a quarterly or annual bonus based on their role and applicable plan. WEX's comprehensive and market competitive benefits are designed to support your personal and professional well-being. Benefits include health, dental and vision insurances, retirement savings plan, paid time off, health savings account, flexible spending accounts, life insurance, disability insurance, tuition reimbursement, and more. For more information, check out the &quot;About Us&quot; section.<p></p>
Pay Range: $185,000.00 - $217,400.00</div>

Senior AI Engineer

700apps

<div>
 We are looking for a
 <strong>
  Senior AI Engineer
 </strong>
 to join our growing technology team and lead the development of advanced AI solutions. In this role, you will design, build, and deploy scalable AI models that power intelligent products and services.
 <br/>
 <br/>
 You will work closely with cross-functional teams to transform complex business challenges into innovative AI-driven solutions.
 <br/>
 <br/>
 <strong>
  Key Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Design end-to-end AI/ML system architecture from data ingestion to deployment and monitoring.
  </li>
  <li>
   Define scalable and reliable ML pipelines.
  </li>
  <li>
   Select the appropriate tools, frameworks, and infrastructure.
  </li>
  <li>
   Ensure performance, security, scalability, and maintainability of AI systems.
  </li>
  <li>
   Design APIs and AI services for integration with products and platforms
  </li>
  <li>
   Collaborate with engineering, product, and data teams to deliver AI-powered features.
  </li>
  <li>
   Develop, train, and fine-tune machine learning and deep learning models.
  </li>
  <li>
   Work on advanced AI solutions such as LLMs, NLP systems, or computer vision models.
  </li>
  <li>
   Optimize models for accuracy, speed, and cost efficiency.
  </li>
  <li>
   Conduct experiments and evaluate model performance using best practices.
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   7+ years of experience in AI / Machine Learning development.
  </li>
  <li>
   Strong programming skills in Python and experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  </li>
  <li>
   Experience with LLMs, NLP, or Generative AI is highly preferred.
  </li>
  <li>
   Experience with MLOps, model deployment, and cloud platforms (AWS, Azure, or GCP).
  </li>
  <li>
   Strong understanding of data structures, algorithms, and software engineering best practices.
  </li>
  <li>
   Excellent problem-solving and communication skills.
  </li>
  <li>
   Experience with cloud platforms such as AWS, GCP, or Azure.
  </li>
  <li>
   Experience with Docker and Kubernetes.
  </li>
  <li>
   Familiarity with MLOps tools such as MLflow, Airflow, or similar.
  </li>
 </ul>
</div>


Valley Bank

<div><div>Responsibilities include but are not limited to:</div>
<ul><li>Design and implement agentic AI workflows using UiPath and Salesforce Agentforce, combining LLMs, rules, APIs, and ML models for end‑to‑end automation.</li>
<li>Develop reusable agent frameworks and components to standardize and accelerate AI solution delivery.</li>
<li>Build, train, and deploy machine learning models (classification, regression, time‑series, anomaly detection) using DataRobot, leveraging Snowflake and Databricks for large‑scale data engineering.</li>
<li>Integrate ML models into enterprise workflows, APIs, and downstream applications.</li>
<li>Engineer integrations across enterprise systems using REST APIs, event-driven architectures, and robust data pipelines.</li>
<li>Support CI/CD and MLOps practices for scalable model deployment, monitoring, retraining, and lifecycle management.</li>
<li>Ensure compliance with AI governance and model risk policies, maintaining monitoring, documentation, and audit readiness.</li>
</ul>Requirements:
<div><div><b>Required Skills:</b></div>
<ul><li>Hands-on experience with agentic AI, orchestration, or intelligent automation platforms (UiPath strongly preferred).</li>
<li>Strong experience building and deploying ML models using DataRobot or comparable platforms.</li>
<li>Solid experience working with Snowflake and/or Databricks for data and ML workloads.</li>
<li>Proficiency in Python; experience with SQL and API-based integrations.</li>
<li>Strong understanding of ML lifecycle, model evaluation, and production deployment.</li>
<li>Exposure to LLMs, prompt engineering, RAG, and AI agents in enterprise environments.</li>
<li>Experience operating AI solutions in regulated industries (financial services, healthcare, etc.).</li>
<li>Familiarity with MLOps, feature stores, and model monitoring practices.</li>
</ul><div><b>Preferred Skills:</b></div>
<ul><li>Experience with Agentic AI and AI workflow orchestration.</li>
<li>Exposure to Generative AI (LLMs, prompt engineering, copilots, or AI assistants).</li>
<li>Experience building or supporting Intelligent Document Processing (IDP) solutions.</li>
<li>Knowledge of OCR, Computer Vision, and document classification/extraction techniques.</li>
<li>Familiarity with Machine Learning concepts, model integration, or ML platforms.</li>
<li>Experience integrating AI and automation solutions with enterprise platforms (e.g., CRM, ServiceNow, core banking systems).</li>
</ul><div><b>Required Experience:</b></div>
<ul><li>Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.</li>
<li>Minimum of 6 years of experience building production-grade AI, ML, or automation solutions and AI Technology.</li>
</ul><div><b>Preferred Experience:</b></div>
<ul><li>Master's in Computer Science, MIS, or related degree.</li>
<li>Financial industry or banking background.</li>
<li>Experience with Salesforce Agentforce or Salesforce platform integrations.</li>
<li>Experience contributing to AI architecture standards or internal platforms.</li>
</ul>
</div><br>
Additional Details : At Valley Bank, we believe in people's growth potential. We invest in it. We protect it. We focus it. For nearly 100 years, we've been the Bank that clients from every industry turn to for our expertise, strategies, and advice-building the kind of trust that can fuel every goal. We are the leading relationship bank built for growth-with over $60 billion in assets, 3,800 experts, and more than 200 consumer branches and commercial banking offices in communities across the US. At Valley, we're all driven by an ambition that goes deeper than just having a job. That's why when you work for us, we make it our goal to help you focus on what drives you-working to turn your passions and strengths into assets you can use to propel your ambitions and build the professional legacy you want. Because when we say we're a relationship bank built for growth, that's not just reserved for our clients-that includes all our associates as well. The Senior AI Engineer will design, build, and operationalize agentic AI workflows and machine learning solutions across the enterprise. This role sits at the intersection of intelligent automation, generative AI, and enterprise data platforms, and will play a key role in scaling AI-driven workflows using UiPath, Salesforce Agentforce, DataRobot, Snowflake, and Databricks. You will partner closely with product, operations, risk, and technology teams to deliver AI systems that are production-grade, governed, and value-driven.<br>
<br>
Pay Transparency In order to support the Fair Compensation Strategy by the US Govt., HR Dept., clients are required to adhere to &quot;Pay Transparency Law&quot;; in the impacted states; that have mandated the employers to list the salary ranges in Job advertisements or postings for job opportunities and Job promotions.</div>

Contour Software

<div><div>About Contour</div><div></div><div><div>
Contour Software</div> has grown from a dozen people to over 2,000 staff across 3 cities, in less than 14 years.</div><div><br>
As a subsidiary of Constellation Software Inc., we are proud to be part of a global enterprise software conglomerate that has grown to become one of the top 10 software companies in the world, with employees and customers in 100+ countries. With a broad-based and ever-growing portfolio of market-leading, vertical-market enterprise solutions covering more than 100 industry domains in predominantly mature markets, CSI's recipe creates the perfect environment for professionals to build fulfilling, long-term careers.</div><div><br>
What started as an R&amp;D &amp; Accounting back-office, has progressed into a full-service Global Centre serving all functions and departments, at the divisional as well as operating group/corporate level. Today Contour employees, located in Karachi, Lahore &amp; Islamabad, are serving CSI divisions located in time zones spanning the globe, from Sydney to Vancouver. With the global growth of Constellation as the wind in our sails, we are only just getting started!</div><div></div><div><div><div>
Job Description: Senior AI Engineer - DIS</div></div><div><div>
The Division:<br>
Dealer Information Systems Corporation (Client) is a leading business management software provider to agricultural, construction, truck refrigeration and lift truck dealers in North America. Founded in 1980, and based in Bellingham WA (USA); we are a team of 100+ professionals who help customers with Software, Hardware and Network Management so they don't have to deal with many vendors but just one full-service company.<br>
<br>
Division Profile: https://www.discorp.com/</div></div><div><div>
The Position</div></div><div><div>
The division is seeking a Senior AI Engineer to join its team. This individual will be responsible for designing and developing the AI platform, including building GenAI systems from the ground up, creating production-ready retrieval-augmented generation (RAG) solutions, developing semantic search and embeddings pipelines, and architecting advanced LLM orchestration layers for complex workflows and agentic systems.</div></div><div></div><div><div><br>
The chosen individual will work out of the Contour Software Lahore or Islamabad resource center office as an extension of the division-based R&amp;D department.</div></div><div></div><div><div><br>
Essential Duties and Responsibilities</div></div><div><ul><li><div>
AI Platform Architecture:</div></li></ul></div><div><ul><li><div>
Design and implement the enterprise GenAI architecture from the ground up.</div></li></ul></div><div><ul><li><div>
Build production-ready RAG systems, semantic search pipelines, embeddings workflows, and vector data infrastructure.</div></li></ul></div><div><ul><li><div>
Architect LLM orchestration layers for multi-step reasoning, tool usage, and AI-driven workflows.</div></li></ul></div><div><ul><li><div>
Define scalable patterns for agentic systems and domain-aware assistants.</div></li></ul></div><div><ul><li><div>
LLM Systems in Production:</div></li></ul></div><div><ul><li><div>
Integrate LLM providers (OpenAI, Anthropic, open-weight models, or hybrid approaches) into secure, observable enterprise systems.</div></li></ul></div><div><ul><li><div>
Build AI service layers, orchestration APIs, caching, evaluation pipelines, and monitoring frameworks.</div></li></ul></div><div><ul><li><div>
Design for latency, cost optimization, safety, and reliability at scale.</div></li></ul></div><div><ul><li><div>
Establish measurable quality benchmarks and evaluation strategies for AI outputs.</div></li></ul></div><div><ul><li><div>
Responsible &amp; Enterprise-Ready AI:</div></li></ul></div><div><ul><li><div>
Implement guardrails, policy enforcement, and hallucination mitigation mechanisms.</div></li></ul></div></div><div><div><ul><li><div>
Define governance standards for data provenance, auditability, and transparency.</div></li></ul></div><div><ul><li><div>
Build AI systems that engineering and compliance teams can trust.</div></li></ul></div><div><ul><li><div>
AI Adoption &amp; Enablement:</div></li></ul></div><div><ul><li><div>
Translate high-impact business problems into AI-native architectures.</div></li></ul></div><div><ul><li><div>
Partner with product leaders to prioritize AI features that drive measurable value.</div></li></ul></div><div><ul><li><div>
Mentor engineers and raise the organization&rsquo;s AI maturity.</div></li></ul></div><div><ul><li><div>
Move teams from PoCs to scalable, production-grade AI capabilities.</div></li></ul></div><div><div>
Required Education and Experience:</div></div><div><ul><li><div>
Bachelor's Degree in Computer Science, Computer Engineering or equivalent technical Degree; or equivalent combination of education and experience.</div></li></ul></div><div><ul><li><div>
5+ years building applied AI/ML systems, with strong recent experience in Generative AI.</div></li></ul></div><div><ul><li><div>
Proven experience shipping LLM-powered applications (RAG, embeddings, prompt strategies, model adaptation).</div></li></ul></div><div><ul><li><div>
Deep understanding of vector search, semantic retrieval, and AI system evaluation.</div></li></ul></div><div><ul><li><div>
Experience building orchestration layers using frameworks such as LangChain, Semantic Kernel, LlamaIndex, or designing equivalent custom architectures.</div></li></ul></div><div><ul><li><div>
Strong cloud-native engineering experience (AWS, Azure, or GCP).</div></li></ul></div><div><ul><li><div>
Advanced Python skills and experience building scalable backend systems and APIs.</div></li></ul></div><div><ul><li><div>
Experience implementing observability, CI/CD, and monitoring for AI systems in production.</div></li></ul></div><div><ul><li><div>
Ability to balance innovation with enterprise constraints (security, compliance, reliability).</div></li></ul></div><div></div><div><div><br>
What Makes This Role Different</div></div><div><ul><li><div>
You are not inheriting a legacy AI stack; you will help define it.</div></li></ul></div></div><div><div><ul><li><div>
You will shape AI standards, architecture, and governance across the division.</div></li></ul></div><div><ul><li><div>
Your work will power real customer-facing products and operational intelligence.</div></li></ul></div><div><ul><li><div>
You will operate at the intersection of AI strategy, architecture, and hands-on engineering.</div></li></ul></div></div><div></div><div><br>
Exciting Benefits we offer:</div><ul><li><div>
Market-leading Salary</div></li><li><div>
Medical Coverage &ndash; Self &amp; Dependents</div></li><li><div>
Parents Medical Coverage</div></li><li><div>
Provident Fund</div></li><li><div>
Employee Performance-based bonuses</div></li><li><div>
Home Internet Subsidy</div></li><li><div>
Conveyance Allowance</div></li><li><div>
Profit Sharing Plan [Tenured Employees Only]</div></li><li><div>
Life Benefit</div></li><li><div>
Child Care Facility</div></li><li><div>
Company Provided Lunch/Dinner</div></li><li><div>
Professional Development Budget</div></li><li><div>
Recreational area for in-house games</div></li><li><div>
Sporadic On-shore training opportunities</div></li><li><div>
Friendly work environment</div></li><li><div>
Leave Encashment</div></li></ul><div></div><div><i>
Disclaimer:</i><i> At Contour, we attribute our success to the unique contributions of our diverse staff. We&rsquo;re committed to fostering a culture of respect that thrives on the varied perspectives and experiences of all individuals we recruit, employ, promote, and compensate. Since day one, we&rsquo;ve adhered to a policy that champions a work environment honoring the worth and dignity of each person while being free from all forms of employment discrimination.</i></div><div></div><div><i>
In our continuous effort to promote inclusivity, we extend our commitment to individuals with special needs by providing reasonable accommodations. We actively encourage qualified individuals with special needs to apply for the various openings within our company. Should you require assistance in completing the application process or have any inquiries regarding special facilities, please do not hesitate to contact our HR team. Your unique talents and abilities are welcomed and valued here.</i></div></div><div></div>

Wells Fargo

<div><p><b>About this role:</b></p><p>
Wells Fargo is seeking a Senior Software Engineer in our <b>Enterprise Data Platforms</b> as part of Consumer Technology. Learn more about the career areas and business divisions at wellsfargojobs.com.</p><p></p><p>
In this position you will design and deliver AI‑powered and agentic solutions that improve SDLC flow, quality, and developer experience across planning, build, test, and delivery. This role partners closely with product, platform, and engineering teams to embed GenAI into tooling, pipelines, and workflows, moving from advisory agile practices to direct, scalable automation. The role serves as both a technical leader and hands‑on engineer, translating AI capabilities into measurable SDLC outcomes.</p><p></p><p><b>
In this role, you will:</b></p><ul><li>
Lead moderately complex initiatives and deliverables within technical domain environments</li><li>
Contribute to large scale planning of strategies</li><li>
Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments</li><li>
Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures</li><li>
Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements</li><li>
Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals</li><li>
Lead projects and act as an escalation point, provide guidance and direction to less experienced staff</li></ul><p><b><br>
Required Qualifications:</b></p><ul><li>
4+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education</li><li>
3+ years of advanced Python development experience building production services, integrating APIs, and managing data pipelines</li><li>
2+ years of experience with either GCP, Azure, Kubernetes, or OpenShift</li><li>
2+ years of experience using Git for source code version control, including branching, pull requests, and collaborative development workflows</li><li>
6+ months of experience developing or deploying AI‑powered tools, chatbots, LLM‑based automation, or agentic workflows, including understanding of AI risks, observability needs, and stakeholder communication</li></ul><p></p><p><b>
Desired Qualifications:</b></p><ul><li>
2+ years of experience with UI/UX - React, Java script, neo4j, MongoDB &amp; Tachyon</li><li>
Strong foundation in building and operating production systems, including distributed services, API‑driven architectures, and CI/CD integrations</li><li>
Demonstrated experience applying Generative AI and/or agentic AI to real‑world workflows, including LLM‑based automation, AI agents, or copilots embedded in developer tools or platforms</li><li>
Experience integrating AI into SDLC tooling such as source control, backlog management, testing frameworks, CI/CD pipelines, or compliance workflows</li><li>
Ability to translate engineering and delivery pain points into AI‑driven solutions with measurable impact (e.g., flow efficiency, quality, cycle time, or developer productivity)</li><li>
Proven collaboration skills working across product, platform, and architecture teams to influence engineering transformation through working software</li></ul><p></p><p><b>
Job Expectations:</b></p><ul><li>
This position is not eligible for Visa sponsorship</li><li>
This position requires a hybrid in office work schedule</li></ul><p></p><p><b>
Job Location</b>:</p><p>
300 S. Brevard - Charlotte, North Carolina 28202</p><p>
1525 W WT Harris Blvd- Charlotte, North Carolina 28262</p></div>

SWATX

<div><p>AI Engineer with strong hands-on experience in end-to-end AI system development, specializing in on-</p><p>
premises and private cloud AI deployments. This role focuses on building production-grade AI solutions using</p><p>
primarily local models, optimizing GPU-based training and fine-tuning pipelines, and developing scalable RAG,</p><p>
agentic, multimodal, and speech-enabled systems.<br>
<br>
Responsibilities
<br>
<br>
Analyze requirements and contribute to technical AI solution design.</p><ul><li>Strong programming skills in Python (mandatory).</li><li>Experience in backend development (APIs, microservices, model serving).</li><li>Hands-on experience with local LLM deployment and optimization.</li><li>Experience in RAG system design and vector databases.</li><li>Practical experience in model fine-tuning (LoRA / PEFT).</li><li>Solid understanding of: Transformer architecture, quantization techniques, and embeddings with retrieval.</li><li>Experience working in Linux environments.</li><li>Participate in peer code reviews and team planning activities.</li><li>Provide task estimations and deliver within approved timelines.</li><li>Apply secure coding practices and participate in bug resolution with quality metrics in mind.</li></ul><p></p><b><br>
Requirements</b><p><br>
Bachelor&rsquo;s degree in computer science, Artificial Intelligence, Data Science, or related discipline.</p><p>
3-5 years of experience in AI Engineering.</p><p>
Proficiency in C#, .NET Core and Python.</p><p>
Experience with Structured and Unstructured databases.</p><p>
Experience with Angular or other frontend technologies is a strong plus.</p><p>
Working knowledge of relational databases (i.e., SQL Server) and non-relational databases (i.e., Qdrant)</p><p>
Familiarity with Git, RESTful services, and Agile development methodologies</p></div><p></p>

FlairsTech

<div>
 <p>
  <strong>
   About the Role
  </strong>
 </p>
 <p>
  <br/>
 </p>
 <p>
  We are hiring an elite cohort of highly hands-on AI Engineers to embed directly within Valsoft's Edelweiss Software Group portfolio of vertical market B2B SaaS companies.
 </p>
 <p>
  We are looking for builders &mdash; engineers who operate as system orchestrators rather than traditional syntax typists. You will design, implement, and deploy secure, enterprise-grade AI systems that automate workflows, eliminate manual processes, rapidly modernize massive legacy codebases, and create measurable business impact.
 </p>
 <p>
  You will work directly with operators, product teams, and leadership to turn inefficiencies into intelligent systems. Operating with a distinct startup mindset within a large-scale corporate portfolio, your primary focus is driving rapid product innovation, executing AI-driven legacy modernization via agentic swarm coding, and maximizing ROI through autonomous multi-agent workflows.
 </p>
 <p>
  If you enjoy owning problems end-to-end, possess a relentless bias toward action, and thrive on shipping real systems into production at an unprecedented velocity, this role is for you.
 </p>
 <p>
  Your mission: act as an organizational force multiplier to increase efficiency, reduce CAC payback periods, increase Net Revenue Retention (NRR), and unlock massive scalability.
 </p>
 <p>
  What You&rsquo;ll Do
 </p>
 <p>
  Build &amp; Ship AI Systems
 </p>
 <ul>
  <li>
   Design, develop, and deploy production-grade, secure AI systems utilizing scalable polyglot microservices.
  </li>
  <li>
   Integrate state-of-the-art enterprise LLMs (Anthropic Claude Opus 4.6, OpenAI GPT-5.2, Google Gemini 3) into SaaS platforms via dynamic, fault-tolerant API routing gateways.
  </li>
  <li>
   Modernize extensive codebases using agentic swarm coding, automated refactoring tools, and cross-language translation.
  </li>
  <li>
   Develop autonomous multi-agent workflows utilizing parallel orchestration tools like the OpenAI Codex and Claude Code CLI.
  </li>
  <li>
   Automate comprehensive technical documentation for legacy and newly generated codebases using AI orchestration.
  </li>
  <li>
   Rapidly prototype &rarr; validate via adversarial testing &rarr; deploy &rarr; iterate.
  </li>
 </ul>
 <p>
  Architect AI Infrastructure
 </p>
 <ul>
  <li>
   Apply good knowledge of software engineering design patterns and architecture to ensure the scalability and maintainability of AI-generated systems.
  </li>
  <li>
   Implement complex RAG systems and continually optimize trade-offs between massive-context hydration (up to 1-million tokens) and multi-stage semantic retrieval.
  </li>
  <li>
   Work extensively with vector databases (Pinecone, Weaviate, FAISS) and manage persistent document embedding queues.
  </li>
  <li>
   Build polyglot microservices specifically capable of handling massive, long-running operational tasks and streaming continuous token generation via persistent connection protocols (WebSockets and Server-Sent Events).
  </li>
  <li>
   Ensure SOC2 compliance, data residency (via inference_geo parameters), and deterministic execution through policy-as-code agentic governance.
  </li>
  <li>
   Deploy and scale models strictly within secure managed cloud boundaries (Azure AI, AWS Bedrock, GCP Vertex) leveraging Docker and Kubernetes orchestration.
  </li>
 </ul>
 <p>
  Transform the Application Lifecycle &amp; Collaborate
 </p>
 <ul>
  <li>
   Architect "zero-touch deployment" CI/CD pipelines fortified with adversarial gating.
  </li>
  <li>
   Design and implement unit test and benchmark automation workflows, utilizing AI agentic coding to rigorously validate and test produced code.
  </li>
  <li>
   Natively integrate synthetic red teaming into CI/CD to actively prevent prompt drift, reward hacking, and logic degradation.
  </li>
  <li>
   Work directly with non-technical stakeholders to translate ambiguous business problems into secure, scalable AI solutions.
  </li>
  <li>
   Optimize Atlassian workflows (Jira) to automate the translation of unstructured product requirements into structured prompt contexts for AI agents.
  </li>
 </ul>
 <p>
  Required Technical Skills
 </p>
 <p>
  Core Engineering
 </p>
 <ul>
  <li>
   5+ years of demonstrable enterprise software development experience.
  </li>
  <li>
   Good knowledge of software engineering design patterns and architecture.
  </li>
  <li>
   Flexible in most popular programming languages (Python, Javascript, Typescript, .Net, C#) and web frameworks (NextJS, etc.).
  </li>
  <li>
   Ability to switch environments and programming using agentic programming tools to validate and test your produced code.
  </li>
  <li>
   Backend development experience designing polyglot APIs, decoupled asynchronous microservices, and utilizing persistent connection protocols (WebSockets/SSE).
  </li>
  <li>
   Familiarity with containerization (Docker, Kubernetes) and architecting multi-region, fault-tolerant cloud infrastructure (AWS, Azure, or GCP).
  </li>
 </ul>
 <p>
  AI &amp; ML Systems
 </p>
 <ul>
  <li>
   Enterprise LLM integration and dynamic API routing (OpenAI, Anthropic, Gemini, DeepSeek).
  </li>
  <li>
   Multi-agent orchestration and advanced CLI tooling (Claude Code with Auto Hot-Reload and Forking Context, OpenAI Codex).
  </li>
  <li>
   Mastery of localized AI IDE layers (Cursor for repository-wide reasoning, GitHub Copilot).
  </li>
  <li>
   Massive-context RAG pipelines, dynamic chunking strategies, and vector databases (Pinecone, Weaviate, FAISS).
  </li>
  <li>
   Custom evaluations (LangSmith), structured outputs, and managed fine-tuning in secure cloud boundaries.
  </li>
 </ul>
 <p>
  MLOps &amp; Process Automation
 </p>
 <ul>
  <li>
   Zero-touch CI/CD pipelines and advanced Git workflows (including Git worktree isolation for autonomous sub-agents).
  </li>
  <li>
   Unit test and benchmark automation frameworks fully integrated with AI-driven testing.
  </li>
  <li>
   Adversarial LLM testing and automated synthetic red-teaming integration.
  </li>
  <li>
   Monitoring dynamic access limits and real-time atomic token/credit consumption tracking.
  </li>
  <li>
   Strict hallucination mitigation, enterprise guardrails, and deterministic policy-as-code execution.
  </li>
 </ul>
 <p>
  Profile We&rsquo;re Looking For
 </p>
 <ul>
  <li>
   Highly hands-on &mdash; you ship, not just design. You operate at an unprecedented velocity by orchestrating advanced autonomous tools.
  </li>
  <li>
   Entrepreneurial startup mindset &mdash; you see legacy inefficiencies and act with a relentless bias toward rapid action.
  </li>
  <li>
   Comfortable with ambiguity and translating complex business needs into precise technical execution.
  </li>
  <li>
   Business-oriented &mdash; you care deeply about ROI, operational leverage, and driving specific financial metrics (CAC, NRR).
  </li>
  <li>
   Fast learner &mdash; keeps up with real-time shifts in AI ecosystems, hardware architectures (e.g., Cerebras chips), and vital API migrations.
  </li>
  <li>
   Pragmatic &mdash; uses the right secure enterprise tool for the specific bottleneck, eschewing the fanciest public tool if it compromises stability or compliance.
  </li>
 </ul>
 <p>
 </p>
</div>


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