Lead AI Software Engineer

Key Responsibilities

Technical Leadership & Team Enablement


*  Act as the technical lead for one or more teams, setting engineering direction and ensuring high technical standards.


*  Provide hands-on architectural guidance, unblocking complex technical challenges, and reviewing critical designs.


*  Mentor Senior and Mid-level Engineers through structured coaching, design reviews, and ongoing technical feedback.


*  Drive and facilitate technical decision-making, including trade-offs between scalability, reliability, cost, and time-to-market.


*  Lead and contribute to lunch & learns, technical deep dives, and internal knowledge-sharing initiatives.


*  Partner with Engineering Managers and Product Leaders to translate business goals into executable technical strategies.


*  Proactively identify gaps in team capability and influence hiring, onboarding, and skill development strategies.

Architecture, Implementation & Quality


* Lead rapid experimentation initiatives, ensuring learnings are clearly documented and communicated to stakeholders.


* Define and standardize testing strategies for AI systems, including unit, integration, regression, and evaluation-based testing.


* Ensure consistency and quality across implementations through code reviews, architectural reviews, and reference implementations.


* Embed deeply in business domains, proactively shaping product direction through technical insight.


* Identify systemic technical issues and drive long-term, sustainable solutions rather than short-term fixes.


* Champion continuous improvement in engineering practices, tooling, and workflows.

 

Required Skills & Qualifications

Technical Expertise


* 6+ years of experience with Python in production environments.


* 3+ years of experience designing, deploying, and operating language model–based solutions in production.


* Strong experience utilizing AI coding Assistants (Github Copilot, Cursor, Claude Code) in daily workflow.


* Working knowledge of emerging AI technologies like MCP, A2A, and GenAI LLM’s.


* Proven ability to develop systems that balance innovation with reliability and maintainability.

 Production & Platform Experience


* Expert-level understanding of software engineering best practices, including architecture patterns, CI/CD, testing, and code quality.


*  Experience designing and operating data pipelines and data management systems at scale.


*  Strong understanding of security, privacy, and compliance considerations in AI-enabled systems.


*  Extensive experience with containers and orchestration in production environments.


*  Ability to diagnose and resolve complex production issues involving AI systems.

Communication & Influence


* Exceptional ability to communicate complex technical concepts clearly to engineers, product leaders, and non-technical stakeholders.


* Comfortable acting as the technic...