Lead the design and implementation of Generative AI services and Agentic workflows that support multiple product features or teams.
Integrate LLMs into applications using modern frameworks, working with APIs or internal model endpoints. Implement telemetry, observability, fallbacks, and cost/latency controls.
Work across data environments to ingest, transform, and serve data for AI use cases, designing practical schemas and retrieval strategies that generalize across environments.
Design and run experiments to compare prompts, models, and configurations; build evaluation flows to measure relevance, safety, robustness, and business impact.
Collaborate with product, data science, design, and domain experts to clarify requirements, break down initiatives into technical plans, and deliver roadmap commitments.
Contribute to and lead code reviews, architecture discussions, documentation, and shared templates/libraries that improve velocity and consistency.
Monitor AI systems in production, participate in incident response, and drive systemic improvements to quality, safety, reliability, and performance.
Partner with security, legal, and compliance to ensure data privacy, responsible AI practices, and regulatory alignment.

Requirements

Degree in Computer Science, Data Science, Software Engineering or related field.
At least 8yrs of professional experience with a Bachelor’s degree or 6 yrs with a Graduate degree
1-year experience in Generative AI technologies (included in the overall professional experience), or 1-2 relevant certifications.
Logical, practical, and innovative problem-solving skills. Can turn ambiguity into architecture, milestones, and explicit tradeoffs.
Strong customer-facing communication: able to lead technical discussions, write clear technical documents, and explain solutions to technical and non-technical audiences.
Shipped and operated LLM-enabled features in production, including evaluation, monitoring, and iteration.
Working knowledge of Generative AI quality and safety practices.
Experience building data-intensive systems end-to-end.
Data engineering fundamentals: ingestion/transforms, maintainable schemas, and retrieval/feature pipelines for analytics and AI.
Strong Python and SQL. Experience integrating services via APIs. TypeScript or other strongly typed language experience is a plus. The ability to learn new tools quickly is required.
Hands-on experience with at least one modern data/analytics platform (e.g., Databricks, Snowflake, Palantir Foundry) and the ability to quickly adapt patterns across other environments.
Ownership mindset with high standards for production readiness and customer outcomes.
Automotive domain knowledge is a plus, not required.
Able to travel as needed for customer and internal collaboration.

Benefits

Pay scale : 120000$ - 145000$ per annum

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Generative AILLMsPythonSQLAPIsdata engineeringdata ingestiondata transformationevaluation metricsTypeScript

Soft Skills

problem-solvingcustomer-facing communicationtechnical documentationcollaborationleadershipinnovationadaptabilityownership mindsetclarifying requirementsincident response

Certifications

Generative AI certificationdata science certificationsoftware engineering certification