๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ฏ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ฏ๐ฌ-๐ฑ๐ฌ ๐๐ฃ๐)
Experience: 10+ yrs
Location: Remote (India)
Job Type: Full-time
We are looking for a highly experienced Senior Technical Lead โ Agentic AI / Generative AI to own the architecture, technical direction, and delivery of production-grade AI solutions. This is a hands-on leadership role for someone who can move seamlessly from early-stage experimentation and prototyping to scalable enterprise production systems.
You will design and build LLM-powered agentic systems, RAG architectures, multi-agent workflows, and AI applications , while mentoring a team of AI/ML and backend engineers. You will also work closely with Product, Data, Platform, Security, and other stakeholders to turn emerging GenAI capabilities into reliable, scalable, and business-ready solutions.
Requirements
Key Responsibilities
AI Architecture & Development
โขArchitect and develop Agentic AI and Generative AI systems from concept through production.
โขBuild multi-step reasoning agents, tool/function-calling workflows, and multi-agent architectures using frameworks such as LangGraph, AutoGen, CrewAI , or custom orchestration.
โขDesign and productionize scalable RAG pipelines , including chunking, embeddings, vector search, and hybrid retrieval.
โขEvaluate and select foundation models based on performance, accuracy, latency, cost, and business requirements.
โขDevelop strategies for prompt engineering, model routing, fine-tuning, and optimization.
Production Engineering
โขOwn technical architecture decisions for scalable, reliable, and cost-efficient LLM applications.
โขEstablish engineering standards covering testing, evaluation, observability, guardrails, hallucination mitigation, and production monitoring.
โขDesign APIs, microservices, and cloud-native architectures supporting AI applications at scale.
โขDrive AI/LLMOps practices across model lifecycle management, deployment, monitoring, and continuous improvement.
Technical Leadership
โขLead, mentor, and develop AI/ML and backend engineers.
โขConduct technical design reviews, architecture discussions, and code reviews.
โขEstablish engineering best practices and promote high standards for production AI development.
โขProvide technical direction while remaining actively involved in complex engineering problems.
Cross-Functional Collaboration
โขPartner with Product, Data Science, Platform, Security, and Compliance teams to deliver AI solutions aligned with business objectives.
โขEnsure AI systems meet appropriate privacy, security, compliance, and responsible-AI requirements .
โขCommunicate complex technical concepts clearly to senior leadership and business stakeholders.
โขRepresent the AI engineering function in strategic discussions around GenAI technology and roadmap decisions.
What's Makes You a Great Fit
โข10+ years of overall software engineering experience , including 4+ years working directly with AI/ML systems.
โขAt least 2+ years of hands-on experience building and deploying LLM-based or agentic AI applications in production .
โขDeep expertise in LLM application development, RAG, embeddings, vector databases, prompt engineering, and AI agents .
โขPractical experience with multi-agent systems, tool/function calling, memory management, planning, and reasoning workflows.
โขStrong Python and software engineering fundamentals with experience building scalable, distributed, production-grade systems.
โขExperience with APIs, microservices, cloud-native architecture, and at least one major cloud platform such as AWS, Azure, or GCP .
โขHands-on experience with MLOps/LLMOps tools such as MLflow, LangSmith, Weights & Biases , or equivalent platforms.
โขWorking knowledge of LLM fine-tuning and evaluation techniques, including LoRA/PEFT, RLHF concepts, and offline/online evaluation frameworks .
โขProven ability to provide technical leadership, mentor engineers, own architecture decisions, and collaborate across teams.
โขStrong communication skills with the ability to translate complex technical concepts into clear business and executive-level discussions.
Good to Have
โขExperience deploying and fine-tuning open-source models such as Llama or Mistral , alongside proprietary models/APIs.
โขContributions to AI/GenAI open-source projects, technical publications, or conference presentations.
โขExperience building AI solutions within regulated industries such as finance, healthcare, or telecom.
โขKnowledge of AI guardrails, red-teaming, responsible AI, and model safety/evaluation frameworks.
โขPrevious formal people-management experience.