AI Engineer Lead - AI Platform (India)

Key Responsibilities

• Own the design and delivery of production AI systems end-to-end, from problem framing and solution architecture to deployment, monitoring, and iteration.
• Lead context engineering for our AI workflows: design how information, instructions, retrieval, and tools are composed so LLM-based systems behave reliably at scale.
• Make technical decisions independently, evaluate tradeoffs, choose architectures, and commit to a direction without requiring escalation for every ambiguity.
• Mentor and unblock junior AI engineers; raise the team's bar on systems thinking, prompt/context design, and software engineering rigor.
• Translate ambiguous business problems into well-scoped, scalable AI solutions, not one-off demos or POCs.
• Operationalize LLMs and AI agents, including prompt orchestration, chaining, evaluation, and observability.
• Build evaluation frameworks to measure and improve reliability, quality, and auditability of AI outputs.
• Apply strong software engineering principles to AI work: code review, testing, CI/CD, monitoring, rollback mechanisms, and maintainable design.
• Collaborate async with US-based engineers, data scientists, and product managers; proactively communicate decisions, blockers, and progress across time zones.
• Hire and grow the India AI team as we scale, setting the standard for what great AI engineering looks like.
• Debug complex issues and perform root cause analysis across model pipelines, infrastructure, and product layers.

Qualifications

• BS or MS in Computer Science, Statistics, or Mathematics, or equivalent experience.
• 6+ years of software engineering experience, including 3+ years building and shipping production AI/ML systems.
• 2+ years of experience leading or managing engineers, you've mentored people, owned delivery for a team, and know how to unblock others because you've repeatedly unblocked yourself.
• Proven track record of building and owning real production systems, not just experiments, notebooks, or demo-ready POCs.
• Deep practical understanding of context engineering: retrieval design, prompt orchestration, tool use, memory, and how to structure LLM systems for reliability and scale.
• Strong understanding of how models work (training, fine-tuning, evaluation), you don't need to train models daily, but you must reason correctly about their behavior and limitations.
• Strong systems thinking: you can take an ambiguous problem, decompose it, and design a scalable, maintainable solution.
• Proficiency in Python with frameworks like FastAPI, PyTorch, or equivalent; experience with LLM frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, and OpenAI/Anthropic APIs.
• Knowledge of RAG architectures, embeddings, reranking models, and LLM-based dialogue and agentic systems.
• Experience building and scaling backend platforms, APIs, and microservices.
• Demonstrated ability to operate autonomously, when you hit an unknown, you navigate it rather than waiting to be told what to do.
• Experience working async or across time zones with distributed teams.
• Frequent user of AI products (Cursor, Claude Code, Copilot, etc.) during the development lifecycle.

Bonus Points

• Experience building agentic systems or LLM-enabled products at meaningful scale.
• Experience growing an engineering team from the ground up (hiring, onboarding, setting standards).
• Familiarity with prompt tuning methodologies and frameworks like DSPy or self-prompting.
• Experience with evaluation-driven development for LLM systems.
• Experience with performance optimization and high-scale document indexing systems.
• Prior startup experience, grit, and ability to thrive in fast-moving, ambiguous environments.
• Familiarity with databases and comfortable writing SQL queries.

What This Role Is NOT

• A pure people-management role. You will write code, design systems, and make technical calls.
• A research or lab role. We ship production systems that real users depend on.
• A task-execution role. We need someone who decides what to build and how, not someone who waits for fully-specified tickets.

Perks

• Competitive Compensation
• Unlimited PTO
• AI Assistants for work (Coding, General Purpose, etc.)