Tech Lead- AI/ML Applications Engineer

Ovii's Interpretation of the Role

We need a senior technical leader to design, build and ship AI‑driven voice and chat bot solutions for enterprise customers. The role owns end‑to‑end production of RAG pipelines, LLM fine‑tuning, and scalable APIs on Kubernetes, collaborating closely with product, data science and DevOps teams.

Role Snapshot

• Lead AI/ML application development
• Design & ship RAG pipelines
• Build scalable FastAPI services
• Deploy models on Kubernetes
• Own end‑to‑end product delivery
• Collaborate cross‑functional teams
• Drive AI architecture decisions

Must-Have Requirements

• Python engineering (5–7 years)
• FastAPI
• LangChain or LangGraph
• RAG pipeline development
• LLM fine‑tuning
• Kubernetes
• MongoDB / PostgreSQL / MySQL
• Python engineering
• LLM fine‑tuning in production
• Kubernetes deployment
• API design and testing

Nice-to-Have Signals

• Voice bot or conversational AI product experience
• MLOps tooling and model observability
• A/B evaluation frameworks
• Voice bot or conversational AI product delivery
• MLOps and model monitoring

Work Setup

• Location: Bengaluru, India
• Work mode: ONSITE
• Employment type: Full-Time

Not Specified in JD

• Visa sponsorship
• Salary range
• Remote eligibility
• Education requirement
• Certifications
• Relocation
• Notice period
• Travel
• Security clearance
• Coding test
• Portfolio
• GitHub
• Writing sample
• Cover letter

What You'll Likely Work On

• Design and implement production‑grade RAG pipelines and fine‑tune large language models for voice and chat bots
• Architect and deliver high‑throughput RESTful APIs with FastAPI, owning the full development lifecycle
• Create multi‑step agentic AI workflows using LangChain or LangGraph
• Productionize AI models on Kubernetes, ensuring reliability, observability and enterprise‑scale performance
• Collaborate with product, data‑science and DevOps teams to shape architecture and roadmap
• Drive AI architecture decisions and mentor teammates as a go‑to engineer
• Own feature delivery from specification through monitoring and continuous improvement

Good Fit If You Have

• Hands‑on experience building voice or conversational AI products at scale
• Familiarity with MLOps tooling, A/B evaluation and model monitoring frameworks
• Ability to quantify project scale (customers served, interaction volume, latency targets)