lead ai engineer

VeeRteq Solutions Inc.

<div><p>We are seeking a high-caliber <b>AI Tech Lead / AI Engineer</b> to design, build, and operationalize agentic AI solutions that accelerate analytics and reporting delivery. This role goes beyond basic agent creation and requires hands-on experience with agent orchestration, memory, and enterprise-grade data access patterns, delivering scalable components that fit into an existing framework while rapidly adapting to incoming business requests.</p>
<p></p><p><b>Responsibilities: -</b></p>
<ul><li>Design, Architect, implement, and iterate on agentic AI solutions to shorten the cycle time for analytics, log analysis, and reporting requests.</li>
<li>Design agent orchestration patterns (multi-agent workflows), tool/function calling, and memory approaches appropriate for enterprise deployments.</li>
<li>Define secure and scalable data access patterns for agents (retrieval, context building, and grounding), integrating with existing data sources and governance expectations.</li>
<li>Partner closely with product, analytics, and engineering stakeholders to intake requirements quickly and deliver working prototypes and production-ready solutions.</li>
<li>Engineer reusable components and best practices that enable scalable delivery (not one-off scripts), aligned to an existing base framework.</li>
<li>Operationalize solutions for reliability and maintainability: testing strategies, monitoring/observability, prompt/version management, and deployment automation.</li>
<li>Evaluate build vs. buy options pragmatically when needed, while keeping focus on shipping solutions on the current platform stack.</li>
</ul><p></p><p><b>Tech Stack (Core): -</b></p>
<ul><li><b>Cloud:</b> AWS (primary deployment environment; open to alternatives)</li>
<li><b>Data/Analytics Platform:</b> Databricks (including native &quot;chat with data&quot; capabilities and potential agent integrations)</li>
<li><b>Agent Frameworks:</b> LangChain, LangGraph</li>
<li><b>Conversational analytics patterns:</b> Ask-questions-on-data / conversational BI approaches (agent-driven analytics and dashboards</li>
</ul><p></p><p><b>Experience: -</b></p>
<p>10+ Years</p>
<p></p><p><b>Location: -</b></p>
<p>Rosemont, IL (3days/Week)</p>
<p></p><p><b>Educational Qualifications: -</b></p>
<p>Engineering Degree BE/ME/BTech/MTech/BSc/MSc.</p>
<p>Technical certification in multiple technologies is desirable.</p>
<p><b>Skills: -</b></p>
<p><b>Mandatory skills</b></p>
<ul><li>Demonstrated experience delivering agentic AI solutions beyond prototypes, including enterprise deployment considerations.</li>
<li>Strong hands-on engineering background with AWS-based deployments.</li>
<li>Experience working with modern data platforms (e.g., Databricks) and integrating LLM solutions with analytics/data ecosystems.</li>
<li>Ability to operate as a senior individual contributor who can define architecture and implement key pieces end-to-end.</li>
</ul><p>Excellent communication and collaboration skills with US-based stakeholders</p>
<p><b>Skills &amp; Expertise Needed</b></p>
<ul><li><b>Agentic </b><b>AI engineering:</b> building and deploying LLM-powered agents for real business workflows.</li>
<li><b>Agent orchestration:</b> designing multi-step and/or multi-agent flows; managing tool use, control flow, retries, and failure handling.</li>
<li><b>Agent memory:</b> short-term and long-term memory patterns; conversation state; summarization and context window management.</li>
<li><b>Enterprise data access patterns for agents:</b> retrieval/grounding strategies; context assembly from structured and unstructured sources; performance-conscious access.</li>
<li><b>Production deployment mindset:</b> security, reliability, monitoring, and maintainability for enterprise-grade AI services.</li>
<li><b>Architecture &amp; best practices:</b> ability to design scalable components that fit into an existing framework and can be extended by the team.</li>
<li><b>Rapid requirements intake:</b> quickly translating ambiguous reporting/analytics asks into implementable solutions and iterating with stakeholders.</li>
<li><b>High autonomy:</b> tech-lead level capability without direct people management; self-directed and able to set engineering direction for the workstream</li>
</ul><p></p><p><b>Good-to-Have Skills</b></p>
<ul><li>Experience implementing retrieval-augmented generation (RAG) and hybrid retrieval across structured/unstructured sources.</li>
<li>Experience with LLMOps practices: prompt/version management, automated evaluation, and regression testing.</li>
<li>Experience building observability for AI systems (quality metrics, traces, latency/cost monitoring).</li>
<li>Familiarity with Databricks-specific agent or model serving patterns (where applicable).</li>
</ul><p>Experience building lightweight analytics experiences on top of agent outputs (e.g., auto-generated insights/dashboards).</p></div>

AI Tech Lead / AI Engineer

Finaira

<div>
 The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives.
 <br/>
 <br/>
 <strong>
  Focus:
 </strong>
 End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship
 <br/>
 <br/>
 <strong>
  The difference you will make:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Provide technical leadership, guidance, and mentorship to a team of AI Engineer
  </li>
  <li>
   Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production
  </li>
  <li>
   Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans
  </li>
  <li>
   Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing
  </li>
  <li>
   Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments
  </li>
  <li>
   Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation
  </li>
  <li>
   Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency
  </li>
  <li>
   Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth
  </li>
  <li>
   Act as a primary technical point of contact for stakeholders regarding AI solutions
  </li>
  <li>
   Hands-on contribution to critical code components, architectural design, and complex problem-solving
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Requirements
  <br/>
  <br/>
 </strong>
 <strong>
  What you will bring to the role:
  <br/>
  <br/>
 </strong>
 <strong>
  Education:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Experience:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Technical Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras)
  </li>
  <li>
   Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving
  </li>
  <li>
   In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes)
  </li>
  <li>
   Strong architectural skills for building robust, scalable, and maintainable AI infrastructures
  </li>
  <li>
   Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services
  </li>
  <li>
   Excellent understanding of data engineering principles, data governance, and database technologies
  </li>
  <li>
   Ability to evaluate and make sound technical decisions on complex trade-offs
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Soft Skills:
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership
  </li>
  <li>
   Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives
  </li>
  <li>
   Strong mentoring and coaching skills, with a passion for developing the talents of junior team members
  </li>
  <li>
   Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships
   <br/>
   <br/>
  </li>
 </ul>
 Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.
</div>


Principal AI Engineer

<div><p>The Principal AI Engineer provides technical leadership and direction for a team of AI Engineer, overseeing the end-to-end development and deployment of significant AI initiatives. This role involves driving technical strategy, setting best practices, mentoring team members, and ensuring the delivery of high-quality, impactful AI solutions that align with business objectives.</p><p></p><p><b><br>
Focus:</b> End-to-End Initiative Leadership, AI/ML Strategy &amp; Mentorship</p><p><b>
The difference you will make:</b></p><ul><li>
Provide technical leadership, guidance, and mentorship to a team of AI Engineer.</li><li>
Architect, design, and oversee the implementation of complex AI/ML systems and platforms from conception to production.</li><li>
Drive the technical roadmap for AI projects, translating business requirements into technical specifications and actionable plans.</li><li>
Champion best practices in AI/ML engineering, MLOps, software development, code quality, and testing.</li><li>
Lead technical discussions, architectural reviews, and problem-solving sessions within the team and across departments.</li><li>
Collaborate closely with product management, data science, and other engineering teams to define project scope, technical feasibility, and resource allocation.</li><li>
Identify and evaluate new technologies, tools, and methodologies to enhance the team's capabilities and efficiency.</li><li>
Conduct performance evaluations and provide constructive feedback to team members, contributing to their professional growth.</li><li>
Act as a primary technical point of contact for stakeholders regarding AI solutions.</li><li>
Hands-on contribution to critical code components, architectural design, and complex problem-solving.</li></ul><br>
<b>
Requirements</b><p><b><br>
What you will bring to the role:</b></p><p><b>
Education:</b></p><ul><li>
Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Master's degree or Ph.D. highly preferred.</li></ul><p><b>
Experience:</b></p><ul><li>
8+ years of extensive experience in AI/ML engineering, with at least 2-3 years in a technical leadership or lead engineer role, successfully leading significant AI projects from end-to-end.</li></ul><p><b>
Technical Skills:</b></p><ul><li>
Expert proficiency in Python and deep expertise in multiple AI/ML frameworks (e.g., TensorFlow, PyTorch, Keras).</li><li>
Demonstrated experience in designing and implementing large-scale, production-grade AI systems, including distributed training and serving.</li></ul><ul><li>
In-depth knowledge and practical experience with MLOps principles, tools, and platforms (e.g., Kubeflow, MLflow, Airflow, Docker, Kubernetes).</li><li>
Strong architectural skills for building robust, scalable, and maintainable AI infrastructures.</li><li>
Proficiency in cloud environments (AWS, Azure, GCP) and their AI/ML services.</li><li>
Excellent understanding of data engineering principles, data governance, and database technologies.</li><li>
Ability to evaluate and make sound technical decisions on complex trade-offs.</li></ul><p><b>
Soft Skills:</b></p><ul><li>
Exceptional leadership, communication, and presentation skills, with the ability to influence and persuade stakeholders at all levels, including executive leadership.</li><li>
Proven ability to think strategically and translate complex business challenges into innovative and impactful data science initiatives.</li><li>
Strong mentoring and coaching skills, with a passion for developing the talents of junior team members.</li><li>
Excellent collaboration and negotiation skills, with the ability to work effectively across diverse, cross-functional teams and build strong relationships.</li></ul><p></p><p>
Finaira is an Equal Opportunity Employer and is committed to providing a workplace free of discrimination and harassment. All employment decisions are based on business needs, job requirements, and individual qualifications, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other status protected by the laws or regulations in the locations where we operate.</p></div>

Inovaqo

<p><b>Job Title:</b> Lead AI Engineer / AI Sales Closer</p><p><b>Location:</b> Onsite (Lahore)</p><p><b>Job Type:</b> Full-Time</p><p><b>About the Role:</b></p><p>We&rsquo;re looking for a <b>technically strong AI professional</b> who can go beyond development and step into a <b>client-facing, revenue-driving role</b>. This position is ideal for someone who understands AI deeply <i>and</i> knows how to <b>sell solutions, not just build them</b>.</p><p>You will be working directly with <b>international clients</b>, leading discovery calls, identifying business problems, and <b>closing deals by presenting tailored AI solutions</b>.</p><p><b>Key Responsibilities:</b></p><ul><li>Lead client calls and <b>act as an AI solutions consultant</b> for international prospects</li><li>Understand client requirements and translate them into <b>practical AI/ML solutions</b></li><li><b>Close leads</b> by confidently presenting value-driven proposals</li><li>Work closely with internal technical teams to align solutions with execution</li><li>Build trust with clients through strong communication and problem-solving</li><li>Contribute to <b>building and scaling the AI department</b></li><li>Stay updated with the latest AI trends to pitch cutting-edge solutions</li></ul><p><b>Requirements:</b></p><ul><li><b>3+ years of proven industry experience</b> in AI/ML</li><li>Strong understanding of AI domains (LLMs, NLP, Computer Vision, etc.)</li><li>Prior experience in <b>client-facing roles, pre-sales, or technical consulting</b></li><li><b>Exceptional communication, presentation, and negotiation skills</b></li><li>Ability to confidently handle international clients and close deals</li><li>Strong business acumen you should understand both <b>tech + revenue impact</b></li></ul><p><b>Preferred:</b></p><ul><li>Experience in AI services companies or startups</li><li>Exposure to SaaS/product-based selling</li><li>Experience working with global clients (US, UK, etc.)</li></ul><p><b>What We Offer:</b></p><ul><li>Attractive salary + closing bonus</li><li>Opportunity to <b>lead the AI function</b></li><li>High-impact role with direct visibility into business growth</li><li>Fast-paced, growth-driven environment</li></ul><p><b>Who This is For:</b></p><ul><li>Someone who thinks: <i><b>&ldquo;I don&rsquo;t just want to build AI&hellip; I want to sell it, scale it, and own it.&rdquo;</b></i></li></ul><p><i><b>To apply: hr@tagsolutionsltd.com</b></i></p><p>Pay: Rs150,000.00 - Rs220,000.00 per month</p><p>Work Location: In person</p>

AI sales closer - Full Stack Engineer

Hex Technologies

SF or NYC
<br><br>
<b>About the role:</b><br>
Come define the future of AI Engineering at the company building the world’s leading agentic data science and analytics platform. As our AI Engineering Lead, you will accelerate the product and company by leveraging frontier AI technology and techniques, collaborating closely with product and engineering, and building and developing a world-class team of AI Engineers.
<br><br>
<b>What you will do:</b><br>
Stay up-to-date on the latest in AI technology and work with engineering teams to push the frontier of product capabilities
<br>Define and implement the future of the AI Engineering function at Hex as we scale
<br>Hire and mentor an exceptional team of AI Engineers
<br>Support an exceptional developer and research experience for teams working with AI technology
<br>Deliver high-performing shared AI infrastructure, including search systems
<br><br>
<b>About You:</b><br>
You have 4+ years of people management experience and leading high-performing teams
<br>You have deep familiarity with modern AI technology as well as classical ML systems and a passion for sharing that with others. Technologies of particular interest include LLMs and transformer models, agentic workflows, context management, and agentic evals.
<br>You are obsessed with driving business outcomes and delivering value to customers
<br>You are rigorous but pragmatic, balancing good experimental design with early-stage agility
<br>You are a strong communicator and love collaborating with other roles and teams to drive outcomes
<br>You are a talent magnet, with the ability to attract and retain exceptional AI talent
<br>Our stack
<br><br>
Our product is a web-based notebook and app authoring platform. Our frontend is built with Typescript and React, using a combination of Apollo GraphQL and Redux for managing application state and data. On the backend, we also use Typescript to power an Express/Apollo GraphQL server that interacts with Postgres, Redis, and Kubernetes to manage our database and Python kernels. Our backend is tightly integrated with our infrastructure and CI/CD, where we use a combination of Terraform, Helm, and AWS to deploy and maintain our stack.
<br><br>
This is a full-time role based out of either our San Francisco or New York office. Employees are encouraged to come into the office at least twice a week, with Tuesdays and Thursdays being our main in-person days.
<br><br>
In addition to our unique culture, Hex proudly offers a competitive total rewards package, including but not limited to, market-benched salary & equity, comprehensive health benefits, and flexible paid time off.
<br><br>
<b>The salary range for this role is:</b> $246,000 - $329,000
<br><br>
The salary range shown may be a reflection of additional factors such as geographical location and skill ranges/levels we’re open to. Placement in the salary range will be decided upon completion of the interview process, taking into account factors like leaving room for growth, internal fairness & parity, your demonstrated skills, and the depth of your experience. Our Recruiting team will be able to provide more details during the interview process.
<br><br>
By submitting an application the candidate consents to the use of their personal information in accordance with the Hex Privacy policy: https://learn.hex.tech/docs/trust/privacy-policy.
<br><br>
About Hex
<br><br>
Hex is growing our team of builders on a mission to make everyone a data person. Our platform solves key pain points with today's data and analytics tooling, and empowers anyone to explore data using natural language, with or without code, on trusted context. Thousands of customers like Ramp, Figma, Stubhub, Anthropic, and Gamma love Hex for our beautiful UI, agentic superpowers, and boundless flexibility.
<br><br>
Hex has raised over $100M from leading investors like Sequoia, a16z, Snowflake and Amplify. With office hubs in San Francisco and New York, as well as remote team members throughout the US and UK, we're a high-agency team that ships fast and has fun doing it. Check out our Intro to Hex video and employee handbook to learn more about what it's like to work at Hex.

AI Engineering Lead

Zoolatech

<div><div><div><div><div><div><div><div>OVERVIEW</div>
</div><div><div>RESPONSIBILITIES</div>
</div><div><div>REQUIREMENTS</div>
</div></div></div></div><div><div><div><p>ATRC's Data &amp; AI Office is a product and platform execution team &mdash; not a traditional enterprise data function. We build and operate AI-enabled systems that create measurable operational impact across the organization. Our primary output is working software in production.</p><p><b>
What we are building &mdash; now:</b></p><ul><li><p>
An executive reporting portal serving senior leadership, integrating live data from SAP, Microsoft 365, SuccessFactors, and internal systems across multiple operational views (finance &amp; budget, KPIs, technology portfolio, news, wellbeing, and a personalized executive home)</p></li><li><p>
A sovereign data and AI platform: data warehouse, governed pipelines, metadata catalog, and classification enforcement across all entities</p></li><li><p>
Data mesh architecture with federated ownership &mdash; each entity owns its data products; the platform provides governed access</p></li><li><p>
Data readiness for the organization's agentic AI platform &mdash; clean, structured, governed data so AI agents can operate on trusted sources</p></li><li><p>
Operational AI agents delivering real value on top of the agentic platform (document triage, anomaly detection, automated briefings, classification automation)</p></li><li><p>
AI-enabled situational awareness and crisis management systems</p></li><li><p>
Data governance and classification &mdash; managing an active external vendor engagement, bridging framework deliverables into platform-enforced rules, and building the ongoing</p><p>
governance operations the organization requires</p></li></ul><p><b>
How we work:</b></p><ul><li><p>
Small team, high ownership &mdash; every engineer owns a module end-to-end</p></li><li><p>
Two-week sprints with demonstrated output at every review</p></li><li><p>
Ship and improve &mdash; working systems beat perfect designs</p></li><li><p>
Core team owns all architecture and product decisions; external capacity executes within defined scope</p></li><li><p>
Decisions take hours, not weeks. Daily technical choices are made by the engineer.</p></li><li><p>
Feature scope decisions take 24 hours. Architecture pivots take 48 hours. Nothing sits in limbo.</p></li><li><p>
Oversee 5 other workstreams powered by 3rd party vendors within the ecosystem but whom we are ultimately accountable for</p></li></ul>
</div><div><p>Builds the AI capabilities that operations depend on &mdash; classification automation, production agents, and the data bridge to the agentic platform.</p><p><b>
Mission</b></p><p>
Build, own, and continuously improve the AI capabilities across the office's production systems, working under the direction of the Principal AI Engineer. Your scope: automated data classification (remediating what's currently broken), AI-generated briefings, and operational AI agents that deliver real value in weeks.</p><p>
An external partner is building an agentic platform that ATRC will use. Your role in that relationship: define the data contracts the platform consumes, evaluate the sample agents delivered, and build the production agents on top of the platform that go beyond demonstrations into real operational use. You don't build the platform &mdash; you make sure ATRC's data is ready for it and that what gets built on top of it actually works.</p><p><b>
What This Role Owns</b></p><ul><li><p>
Data classification automation: implementing automated classification to remediate current failures, embedding classification into data pipelines alongside the Governance</p></li><li><p>
Lead Operational AI agents: building production agents on top of the agentic platform &mdash; going beyond the sample agents the external partner delivers into real operational workflows</p></li><li><p>
Agentic platform data contracts: defining what data the platform needs, in what format, with what quality guarantees &mdash; working with the Principal AI Engineer</p></li><li><p>
AI service implementation: FastAPI service around LLM APIs with versioned prompt templates</p></li><li><p>
Classification and briefing prompts: structured prompts returning validated JSON with tags, confidence levels, source attribution</p></li><li><p>
Prompt versioning: templates in configuration, editable without code changes</p></li><li><p>
Observability: every LLM call logged with input hash, model version, output, latency, token count</p></li><li><p>
Fallback logic: graceful degradation when LLM APIs are unavailable</p></li><li><p>
Quality evaluation: running precision/recall evaluations against human reviewer samples, reporting results, iterating prompts</p></li></ul><p><b>
Key Decisions</b></p><ul><li><p>
Prompt implementation &mdash; few-shot examples, output parsing, error handling</p></li><li><p>
Confidence threshold tuning based on evaluation results</p></li><li><p>
Context window packing &mdash; what data fits within token budgets</p></li><li><p>
Fallback behavior when APIs degrade</p></li><li><p>
Agent evaluation &mdash; whether an external partner's sample agent is production-ready or needs rework</p></li><li><p>
Bug triage for AI components &mdash; autonomous fix vs. escalate to Principal AI Engineer</p></li></ul><p><b>
Does Not Do</b></p><ul><li><p>
Define AI architecture or agent design patterns (Principal AI Engineer)</p></li><li><p>
Build the agentic platform itself (external partner)</p></li><li><p>
Build the backend API or data pipelines</p></li><li><p>
Fine-tune or train models</p></li><li><p>
Define governance policies (Governance Lead)</p></li></ul><p><b>
Ideal Candidate</b></p><p>
Has shipped an LLM-based feature that non-technical users depend on daily &mdash; and has been responsible when it breaks. Knows the hardest part of applied AI is the fallback, the observability, and the human review loop &mdash; not the prompt. Can evaluate someone else's agent demo and quickly identify whether it's production-ready or held together with string. Works well under a senior AI lead &mdash; takes architectural direction and executes with high quality and speed. Not attached to a particular model &mdash; the job is reliable output.</p>
</div><div><ul><li><p>LLM APIs (Claude, GPT-4, open-weight models) &mdash; structured output, JSON mode, system prompts</p></li><li><p>
Prompt engineering for classification &mdash; zero-shot and few-shot</p></li><li><p>
Python &mdash; async API calls, retry logic, exponential backoff</p></li><li><p>
LLM evaluation &mdash; precision/recall, human-AI agreement scoring</p></li><li><p>
Structured output &mdash; JSON schema enforcement, Pydantic validation</p></li><li><p>
Open-weight / sovereign model APIs (Falcon, Llama, or equivalent)</p></li><li><p>
Token budgeting and context window management</p></li><li><p>
AI observability &mdash; output quality monitoring, anomaly detection</p></li><li><p>
FastAPI and Docker</p></li></ul>
</div></div></div><div><div><div><div><p>Location:
</p><div>Istanbul, Turkey
</div></div><div><p>Seniority:
</p><div>Senior
</div></div><div><p>Technologies:
</p><div>Python
</div></div></div></div><div><div><p>Benefits:
</p><ul><li><b>Paid Vacation
</b></li><li><b>Hybrid Work (home/office)
</b></li><li><b>Sick Days
</b></li><li><b>Sport/Insurance Compensation
</b></li><li><b>Holidays Day Off
</b></li><li><b>English Classes
</b></li><li><b>Training Compensation
</b></li><li><b>Transportation compensation</b></li></ul></div></div></div></div></div></div>

AI Engineer

Arize AI

<div><div><div>Location</div>
<div>EMEA (Remote)</div>
</div><div><div>Status</div>
<div>Full time</div>
</div><div><div>Department</div>
<div>Sales Engineering</div></div></div>
<br><div><div><div><div>About Arize</div>
<p>
AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That&rsquo;s where we come in. Arize AI is the leading AI &amp; Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace&mdash;so teams can ship faster with confidence.</p>
<p>
We&rsquo;re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.</p></div><div><b>
The Team</b></div>
<p>
Our engineering team builds systems that interact with some of the most complex software ever deployed in production. The team is composed of industry veterans that have built deep learning infrastructure, autonomous drones, ridesharing marketplaces, ad tech and much more. We are looking for an AI Sales Engineer (Solutions Architect) to join the good fight and get this product in the hands of every AI/ML organization.</p>
<p>
You'll work side-by-side with our Account Executives to articulate the Arize value and overall strategy to differentiate the platform throughout the sales process and drive POCs from requirements gathering to close. The activities performed by an AI Sales Engineer are diverse - one day you might be assisting with a high-level pitch of Arize to a CDO, and the next day you might be working hands-on to develop a small proof of concept.</p>
<div><b>
What You&rsquo;ll Do</b></div>
<p>
You are the trusted advisor to the customer:</p>
<ul>
<div>Partner with our account executives to articulate the overall Arize value proposition, vision, and strategy to customers</div>
<div>Work closely with some of the most sophisticated GenAI teams in the world.</div>
<ul><div>You will act as a trusted advisor to our prospective customers, while also building relationships with technical and business stakeholders.</div>
</ul><div>Lead product demonstrations of the Arize platform</div>
<ul><div>Advise on GenAI and ML best practices</div>
</ul><div>Lead discovery to understand prospect&rsquo;s GenAI tech stack to collaborate with the Sales team to construct a compelling value proposition of the Arize Platform</div>
<div>Lead Proof of Concept (PoC) motions with prospective buyers</div>
<div>Handle technical objections and develop strategies across sales, engineering, and product to unblock them</div>
</ul><div><b>What We&rsquo;re Looking For</b></div>
<p><i>
Note: Even if you do not check every single box, we still encourage you to apply!</i></p>
<ul>
<div>3+ years of experience in a customer-facing role such as sales engineer, solutions engineer, or forward deployed engineer</div>
<div>Strong communication skills: Ability to simplify complex, technical concepts</div>
<div>Proficiency in Python / Typescript</div>
<div>Knowledge of LLM / Agentic frameworks such as OpenAI Agents SDK, Google ADK, LangGraph, and DSPy</div>
<div>Understanding of GenAI concepts and application evaluation + development lifecycle</div>
<div>A quick and self learner - undaunted by technical complexity of production AI deployments and welcome the challenge to learn about them and develop your own POV.</div>
</ul>
<p>Bonus Points, But Not Required</p>
<ul>
<div>Previous experience working across and aligning Sales, Product, and Engineering</div>
<div>Previous experience within a team that underwent a high growth stage</div>
<div>Previous engineering experience in: Data Engineering, MLOps, Kubernetes, GCP / AWS / Azure</div>
</ul>
<p>Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes unlimited paid time off, generous parental leave plan, and others for mental and wellness support.</p><div><div>
More About Arize</div>
<p>
Arize&rsquo;s mission is to make the world&rsquo;s AI work&mdash;and work for people.<br>
Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge&mdash;understanding whether AI is performing and how to improve it at scale.</p>
<p>
Learn more about what we're doing here:</p>
<p>
https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/</p>
<p>
https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/</p>
<p>
Diversity &amp; Inclusion @ Arize</p>
<p>
Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture</p>
<ul>
<div>Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI</div>
<div>Culturally conscious events such as LGBTQ trivia during pride month</div>
<div>We have an active Lady Arizers subgroup</div>
</ul></div></div><div></div><div><div><div><div><div><div>Apply now</div></div></div></div></div></div></div><p></p>

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