Company: Tenarai

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Enterprise

Company Type: Product & Service

Business Model: B2B

Funding Stage: Series B

Industry: Information Technology

Salary Range: ₹ 25-45 Lacs PA

Role Overview

- Lead the development and deployment of enterprise AI/ML solutions.
- Work closely with Microsoft / McKinsey technical and architecture teams.
- Translate architectural designs into scalable, production-ready systems.
- Build LLM and Agentic AI applications.
- Technically validate and challenge architecture decisions.
- Lead engineers while remaining hands-on with coding and implementation.
- Ensure strong engineering practices, quality, security, scalability, and reliability.

Key Responsibilities

- Lead AI/ML solution build, deployment, and implementation.
- Supervise and mentor the engineering team.
- Review and validate architecture proposed by external partners/architects.
- Translate architecture and design patterns into production implementations.
- Build reusable frameworks, core components, and reference implementations.
- Own code quality, testing, engineering standards, and MLOps.
- Conduct code reviews and establish best practices.
- Implement Git, CI/CD, secure coding, testing, and evaluation practices.
- Identify technical risks, dependencies, and design gaps.
- Lead development of:
- LLM applications
- RAG solutions
- AI Agents / Agentic AI
- LLM orchestration
- Tool/function calling
- LLM evaluation frameworks

- Provide technical guidance and mentorship.
- Support knowledge transfer to client/AM teams.
- Ensure solutions are production-ready, scalable, secure, reliable, and maintainable.

Required Skills & Experience

- 8–11 years of experience in Software Engineering, AI Engineering, or ML Engineering.




- Strong recent hands-on coding experience.
- Strong Python proficiency.
- Strong experience with TensorFlow and/or PyTorch.
- Proven experience building and deploying LLM / Generative AI / Agentic AI solutions in production.
- Hands-on experience with:
- RAG
- LLM Orchestration
- AI Agents / Agentic Workflows
- Tool / Function Calling
- Prompt Engineering
- LLM Evaluation

- Solid software engineering fundamentals:

- Clean code
- Unit & integration testing
- Git / Version Control
- CI/CD
- Secure coding
- Code reviews
- MLOps

- Experience leading or supervising engineering teams.
- Ability to evaluate and technically challenge architecture.
- Strong problem-solving and stakeholder management skills.
- Excellent communication skills.
- Ability to take end-to-end ownership.

Good to Have

- Azure AI Foundry
- Azure OpenAI
- LangChain
- LangGraph
- Semantic Kernel
- AutoGen
- Microsoft Azure / Cloud AI platforms
- Docker / Kubernetes
- Enterprise or manufacturing experience
- Partner/vendor-led architecture experience
- Compliance, security, governance, or regulated-environment exposure
- Experience mentoring client teams

Mandatory Technical Skills

- Python
- TensorFlow / PyTorch
- Generative AI / LLM
- RAG
- AI Agents / Agentic AI
- LLM Orchestration
- Tool / Function Calling
- LLM Evaluation
- Software Engineering
- CI/CD
- MLOps
- Git / Version Control

Ideal Candidate The ideal candidate should be a hands-on AI/ML Technical Lead who can:

- Build production-grade AI solutions.
- Lead and mentor engineering teams.
- Challenge and validate complex technical architectures.
- Bridge the gap between architecture and implementation.
- Establish strong engineering and MLOps practices.
- Work effectively with architects, clients, partners, and engineering teams.
- Take complete ownership of technical delivery.

📌 Technical Lead (Bengaluru)
🏢 Sourcingxpress
📍 Bengaluru