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    Job · 12969696

    SourcingXPress logo

    Technical Lead

    SourcingXPress · Not specified · onsite · Posted 60d ago

    Undisclosed8–11 yrsfulltimeSourced fromLinkedIn

    About a minute. You'll make an account on the way through.

    About this role

    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 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.

    Sourced from linkedin

    Skills

    DockerKubernetesAimlRetrieval Augmented GenerationAutoGenPrompt EngineeringLLM orchestrationAzure AI FoundryMLOpsUnit testingSemantic KernelAzure OpenAIClean Codecode reviewsLarge Language Models (LLMs)LLM EvaluationPytorchTensorflowsecure codingtool function callingPythonIntegration TestingMicrosoft AzureLanggraphLangchainAgentic AiGITCi/Cd

    Technical Lead · waiting for your command