Technical Lead

SourcingXPress; Mumbai; On-site; INR 2,500,000 - 4,500,000; Full time

Job summary

Tenarai is seeking a senior AI/ML engineering leader to drive enterprise AI/ML initiatives and hand‑on implementation. You will collaborate with Microsoft/McKinsey teams to translate designs into scalable, production-ready systems. The role emphasizes leading engineers while maintaining hands‑on coding, ensuring security and reliability.

You will build LLM and agentic AI applications, validate architectures, and uphold strong MLOps practices across the stack.

Qualifications

• 8-11 years of experience in Software/AI/ML Engineering.
• Strong Python proficiency.
• Experience with TensorFlow and/or PyTorch.
• Proven track record building and deploying LLM/Generative AI in production.
• Hands-on with RAG, LLM orchestration, AI agents/workflows, tool calling, prompt engineering, and LLM evaluation.
• Strong software engineering fundamentals: clean code, tests, Git, CI/CD, secure coding, code reviews, and MLOps.
• Experience leading or supervising engineering teams.

Responsibilities

• Lead AI/ML solution build, deployment, and implementation.
• Mentor and supervise the engineering team.
• Review and validate architecture from partners/architects.
• Translate architecture/design patterns into production implementations.
• Develop reusable frameworks and reference implementations.
• Own code quality, testing, and engineering standards (MLOps).
• Conduct code reviews and establish best practices.
• Implement CI/CD, secure coding, testing, and evaluation practices.
• Identify risks, dependencies, and design gaps.
• Lead development of LLM apps, RAG solutions, AI agents, and orchestration.

Skills

Python

TensorFlow

PyTorch

Generative AI

LLM Orchestration

RAG

AI Agents

Tool Calling

MLOps

CI/CD

Git

LangChain

LangGraph

Azure AI

Leadership

Tools

Python IDEs & frameworks

Docker

Kubernetes

Azure OpenAI

Azure AI Foundry

Job description

Job Description

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

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

Ideal Candidate

• 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.