About Us
We intend to defy the cliches while living them. Change the world working for a scrappy, data-driven, and customer-focused startup that's revolutionizing financial workflows using AI. You will be instrumental in shaping this cutting edge AI product, owning solutions from design to launch.
We're looking for a technical AI Lead to anchor and grow our AI engineering team in India. This is not a people-management-only role, we need a hands-on technical leader who has built and owned production AI systems, can design scalable solutions from ambiguous problem statements, and can unblock both themselves and their team without waiting for direction.
As the AI Lead at Genios, you'll be the senior-most technical decision-maker for AI in our India team. You'll work closely with our US-based AI team while operating with high autonomy across time zones. You'll mentor and grow junior engineers, set the technical bar, and remain deeply hands-on, designing context engineering strategies, architecting AI systems, and shipping production-grade features yourself.
This role requires ownership, technical depth, sound judgment, and the ability to lead through doing, not just delegating.
Note: This is a hybrid position based in India, requiring strong async collaboration with US-based teams and periodic overlap hours.
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.)
