Technical Lead

Company: Tenarai

Website: Visit Website

LinkedIn: Visit LinkedIn

Business Type: Enterprise

Company Type: Product & Service

Business Model: B2B

Funding Stage: Series A

Industry: Information Technology

Salary Range: ₹ 25-45 Lacs PA

Job Description 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

• Strong 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

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.