Founding AI Engineer - Agents, LLM Systems & Applied Research

Role:Founding AI Engineer - Agents, LLM Systems & Applied ResearchType:Full-time · Core Platform TeamLocation:Delhi NCR (immediate joiners preferred)Experience: 5-7 years total · 2–3+ years in production AI/ML systemsReports to:CTO
ABOUT SUTRA.AISutra.AI is an AI transformation platform purpose-built for mid-market businesses, teams that want enterprise-grade AI outcomes without building a large AI organization. The platform orchestrates end-to-end:data → opportunities → projects → production apps/APIs, with value tracking built in.We've been building for 3+ years, launched out of stealth recently, and already have dozens of customers with millions of dollars in measurable ROI. We're in scale-up mode - shipping fast, standardizing platform engineering patterns that compound across every customer and product line.
ABOUT THE ROLEWe're hiring anFounding AI Engineerto own the execution of our AI systems end-to-end.This is the execution backbone of our AI platform. You'll architect and ship production systems, set engineering standards, and work directly with founders on high-priority initiatives. You'll turn ambiguous problems into scalable solutions, independently, with minimal oversight.This is not a research role. Not a coordination role. This is a builder + owner role.The systems you build will be used by the entire team. The patterns you establish will be replicated across the organization. High-leverage by design.
WHAT YOU'LL DO• Design and implement production AI systems: RAG pipelines, agent frameworks, LLM orchestration,evaluation harnesses• Own the full lifecycle: problem scoping → prototyping → production deployment → monitoring and iteration• Build scalable backend systems in Python - APIs, async workflows, data pipelines• Establish engineering standards and best practices across the AI platform• Lead execution across junior engineers: code reviews, unblocking, technical guidance• Set up evaluation frameworks to measure accuracy, latency, cost, and reliability• Debug complex issues across layers: data quality, model behavior, infrastructure, system design• Collaborate cross-functionally with product, founders, and customers on roadmap and technical decisions
REQUIREMENTSMust-Haves• 4-7 years total software engineering experience• 2-3+ years building production AI/ML systems (not just research or experiments)• Strong backend engineering skills: Python, APIs, async systems, distributed architectures• Proven track record of end-to-end ownership - shipped systems independently from idea to production• LLM systems: RAG, prompting, agents, evaluation, embeddings, retrieval• LLM orchestration: LangChain, LangGraph, LlamaIndex, or equivalent• Cloud AI platforms: AWS Bedrock, Vertex AI, Azure OpenAI, or equivalent• Vector databases and retrieval systems: Pinecone, Weaviate, Qdrant, or similar• Data pipelines: ETL, batch/stream processing• System design and scalability thinking - build for production, not local prototypes• Strong analytical and debugging skills: root cause analysis, not quick fixes• Team-oriented mindset: mentor others, prioritize company impact, low ego
Preferred• Experience from high-ownership environments: startups or fast-moving product companies• LLM fine-tuning or training experience• Familiarity with data platforms: Trino, Spark, Airflow, dbt• Open-source contributions or published technical writing
WHY JOIN US• High ownership: own systems end-to-end without constant oversight• High leverage: everything you build gets reused; every pattern you set gets replicated• Core team: direct impact on company direction and technical decisions• Hard problems: build production AI systems at scale, not demos• Early stage: shape the engineering culture, tech stack, and product direction