Job for Tech Lead – AI Agent Development

2 Months ago • 7 Years + • Research Development

Job Summary

Job Description

The AI Tech Lead will spearhead a team focused on multi-agent AI products. Responsibilities include leading intelligent agent systems, designing RAG pipelines, optimizing embedding strategies, overseeing agent frameworks, setting best practices, leading experimentation, and collaborating with teams. The role offers the opportunity to build end-to-end AI solutions that continuously learn and adapt.
Must have:
  • Strong command of Python with frameworks like LangChain.
  • Deep understanding of text embeddings and vector math.
  • Proficient in vector database integration.
  • Experience building scalable RAG pipelines.
  • Solid grasp of agent memory architectures.
  • Knowledge of prompt engineering techniques.
  • Comfortable deploying LLM-based solutions.
Good to have:
  • Familiarity with self-hosted LLMs.
  • Experience in real-time AI applications.
  • Knowledge of AutoGPT or similar frameworks.
  • Exposure to data annotation or custom embedding training.
  • Prior team management experience (5+ members).
Perks:
  • 100% Remote | Flexi-Hours | Global Project Exposure
  • High-impact role at the forefront of GenAI evolution
  • Opportunity to build core IP and AI product lines
  • Performance bonuses and long-term leadership track
  • Supportive leadership + global engineering collaboration

Job Details

Experience: 7+ Years (AI/ML/NLP), 3+ Years in GenAI/LLM Applications

About Mobiloitte

Mobiloitte is a full-stack digital transformation company with global operations across India, UAE, Singapore, UK, USA, and South Africa. We are rapidly expanding our AI division with a focus on intelligent agent systems, LLM integrations, and context-aware automation. We seek a seasoned AI Tech Lead to spearhead a dynamic and growing team shaping the future of multi-agent AI products.

Role Overview

We are looking for a Tech Lead – AI Agent Development with deep hands-on expertise in building, scaling, and managing LLM-based agent architectures. This role requires both strong leadership and deep technical mastery in modern NLP paradigms, embedding techniques, and Retrieval-Augmented Generation (RAG) systems.

The role offers the opportunity to build end-to-end AI solutions that continuously learn and adapt – powering intelligent agents deployed across enterprise and consumer domains.

Key Responsibilities

  • Lead and architect intelligent agent systems using LangChain, LlamaIndex, or similar LLM frameworks.
  • Drive the design and implementation of advanced RAG pipelines, from chunking strategy to prompt templating.
  • Optimize embedding generation, storage, and retrieval strategies using vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
  • Oversee modular agent frameworks for task automation, memory handling, tool orchestration, and reasoning workflows.
  • Set best practices for chunking logic, token optimization, prompt compression, and data formatting for optimal contextualization.
  • Lead experimentation in agent self-refinement, feedback loops, and continuous learning paradigms.
  • Collaborate with product owners, backend, and DevOps teams to integrate AI solutions into scalable architectures.
  • Manage and mentor a growing team of AI developers, data scientists, and NLP engineers.
  • Stay abreast of the latest in open-source models, agentic workflows, and GenAI frameworks.

Must-Have Technical Skills

  • Strong command over Python, with hands-on experience in frameworks like LangChain, LlamaIndex, Transformers (HuggingFace).
  • Deep understanding of text embeddings (OpenAI, Cohere, Sentence-BERT), vector math, and high-dimensional similarity search.
  • Proficient in vector database integration (Pinecone, FAISS, Weaviate, Qdrant, or Chroma).
  • Experience building scalable RAG pipelines, including custom chunkers, retrievers, and context optimizers.
  • Solid grasp of agent memory architectures, dynamic tool calling, and planning/action chaining.
  • Knowledge of prompt engineering, structured prompting, few-shot/coT techniques.
  • Comfortable deploying LLM-based solutions in real-world production environments, including prompt monitoring, latency tuning, and fail-safes.

Preferred/Bonus Skills

  • Familiarity with self-hosted LLMs (Mistral, LLaMA2/3, Claude, Mixtral, Phi-2).
  • Experience in real-time AI applications, low-latency APIs, and streaming responses (LangChain Streaming).
  • Knowledge of AutoGPT, BabyAGI, Open Agents, or similar experimental frameworks.
  • Exposure to data annotation, knowledge distillation, or custom embedding training.
  • Prior team management experience (5+ members) with sprint planning, code reviews, and mentorship.

Soft Skills & Leadership Traits

  • Ability to drive experimentation while maintaining architectural discipline.
  • Strategic mindset: balance between rapid PoCs and long-term scalability.
  • Excellent communication – technical, cross-functional, and client-facing.
  • Bias for action – a builder and problem-solver with high ownership.

Engagement & Benefits

  • 100% Remote | Flexi-Hours | Global Project Exposure
  • High-impact role at the forefront of GenAI evolution
  • Opportunity to build core IP and AI product lines
  • Performance bonuses and long-term leadership track
  • Supportive leadership + global engineering collaboration

How to Apply

If you’re ready to build the next generation of autonomous, intelligent AI agents, let’s connect.

Complete Registration Form:

Send your updated resume and GitHub/portfolio to [careers@mobiloitte.com]

Apply directly at  www.mobiloitte.com/careers

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About The Company

At Mobiloitte, we lead digital transformation with AI-first applications across Blockchain, Mobile, Web, IoT, Gaming, and the Metaverse. Our industry-focused solutions leverage the power of AI, Blockchain, Data, and Cloud to drive success and innovation. By combining advanced AI with secure Blockchain and advanced mobile and web development, we empower industries to thrive in today’s fast-evolving digital landscape.

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