About Exponentia.ai

Exponentia.ai is a fast-growing AI-first technology services company, partnering with enterprises to shape and accelerate their journey to AI maturity. With a presence across the US, UK, UAE, India, and Singapore, we bring together deep domain knowledge, cloud-scale engineering, and cutting-edge artificial intelligence to help our clients transform into agile, insight-driven organizations.

We are proud partners with global technology leaders such as Databricks, Microsoft, AWS, and Qlik, and have been consistently recognized for innovation, delivery excellence, and trusted advisories.

Awards & Recognitions:

- Innovation Partner of the Year – Databricks, 2024
- Digital Impact Award, UK – 2024 (TMT Sector)
- Rising Star – APJ Databricks Partner Awards 2023
- Qlik’s Most Enabled Partner – APAC

With a team of 450+ AI engineers, data scientists, and consultants, we are on a mission to redefine how work is done, by combining human intelligence with AI agents to deliver exponential outcomes.

Learn more: www.exponentia.ai

About the Role:

The ideal candidate should possess strong expertise in Python, Generative AI frameworks, LLM orchestration, vector databases, cloud-native architectures, and MLOps practices. This role requires a hands-on technical leader who can drive innovation, mentor engineering teams, and collaborate with cross-functional stakeholders to deliver production-ready AI solutions.

You will play a key role in designing and implementing AI systems such as:

- RAG (Retrieval-Augmented Generation) applications
- AI Agents and multi-agent workflows
- Conversational AI platforms
- Enterprise copilots
- Intelligent document processing solutions
- LLM fine-tuning and evaluation pipelines

Strong problem-solving skills, architectural thinking, and experience building scalable AI products are critical for success in this role.

Key Responsibilities

Technical Leadership

- Lead the architecture, design, and development of enterprise-scale Generative AI and LLM-based applications.
- Define technical strategy, engineering standards, and AI development best practices across projects.
- Drive technical decision-making for scalable, secure, and high-performance AI systems.
- Mentor and guide AI/ML engineers through code reviews, design discussions, and technical coaching.
- Collaborate with product managers, architects, and business stakeholders to translate business requirements into AI solutions.

Generative AI & LLM Engineering

- Design and implement advanced AI solutions using LLMs, RAG architectures, AI agents, and prompt engineering techniques.
- Build intelligent AI workflows using frameworks such as LangChain, LlamaIndex, CrewAI, or similar orchestration platforms.
- Develop scalable pipelines for:
- Embeddings generation




- Semantic search
- Context retrieval
- Document ingestion
- Model inference
- Evaluation and monitoring

- Optimize prompts, retrieval strategies, and model performance for accuracy, latency, and cost efficiency.
- Work with proprietary and open-source LLMs including OpenAI, Claude, Llama, Gemini, or Mistral models.

AI Platform & Backend Engineering

- Build and maintain scalable AI APIs and microservices using Python frameworks such as FastAPI or Flask.
- Design distributed and cloud-native architectures for AI applications.
- Integrate vector databases, caching systems, and data pipelines into AI ecosystems.
- Ensure high availability, observability, scalability, and security of AI platforms.

MLOps / LLMOps

- Lead deployment and operationalization of AI models in production environments.
- Implement CI/CD pipelines for AI workflows and automated model deployment processes.
- Establish monitoring, logging, evaluation, and governance frameworks for LLM applications.
- Improve model lifecycle management, experimentation tracking, and infrastructure automation.

Collaboration & Delivery

- Work closely with cross-functional teams including Data Science, Engineering, Product, and DevOps.
- Participate in sprint planning, estimation, architecture reviews, and technical roadmap discussions.
- Identify technical risks and propose scalable solutions proactively.
- Stay updated with emerging AI trends, frameworks, and best practices to drive continuous innovation.

Ideal Candidate Profile

- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 8+ years of overall software engineering experience with at least 4+ years in AI/ML and Generative AI development.
- Strong programming expertise in Python with experience building production-grade applications.
- Hands-on experience with Large Language Models (LLMs), Generative AI, and Retrieval-Augmented Generation (RAG) systems.
- Proven experience working with AI orchestration frameworks such as: LangChain, LlamaIndex, CrewAI, Semantic Kernel
- Experience integrating and working with models from: OpenAI, Anthropic Claude, Gemini, Llama, Mistral
- Strong understanding of: Prompt Engineering, Embeddings, Vector Search, Semantic Retrieval, AI Agents, Fine-tuning and evaluation techniques
- Experience with vector databases and search technologies such as: Pinecone, Weaviate, FAISS,



ChromaDB, Elasticsearch / OpenSearch
- Expertise in backend/API development using: FastAPI, Flask, REST APIs, Microservices architecture
- Experience with cloud platforms: AWS, Azure, Google Cloud Platform (GCP)
- Hands-on experience with: Docker, Kubernetes, CI/CD pipelines, Git-based workflows
- Solid knowledge of MLOps / LLMOps practices including deployment, monitoring, evaluation, and observability.
- Understanding of scalable system design, distributed systems, and performance optimization.
- Excellent communication, stakeholder management, and technical leadership skills.
- Experience leading technical teams and mentoring engineers in Agile/Scrum environments.

Preferred Qualification

- Experience building and deploying enterprise-scale Generative AI products in production environments.
- Hands-on experience with AI agents, multi-agent orchestration frameworks, and autonomous workflows.
- Exposure to fine-tuning, parameter-efficient tuning (LoRA/PEFT), and custom model training techniques.
- Experience with model evaluation frameworks, guardrails, hallucination detection, and Responsible AI practices.
- Familiarity with AI security, governance, compliance, and data privacy standards.
- Experience working with multimodal AI solutions involving text, image, audio, or video models.
- Knowledge of data engineering and streaming technologies such as Kafka, Spark, or Airflow.
- Exposure to GPU infrastructure, model optimization, and inference acceleration techniques.
- Experience integrating AI solutions with enterprise systems such as CRM, ERP, or workflow platforms.
- Contributions to open-source AI projects, research publications, patents, or technical blogs are a plus.
- Cloud, AI, or Kubernetes certifications are an added advantage.
- Prior experience in client-facing or consulting engagements is preferred.
- Strong analytical mindset with the ability to solve complex business and technical challenges

Why Join Exponentia.ai?

- Innovate with Purpose: Opportunity to create pioneering AI solutions in partnership with leading cloud and data platforms
- Shape the Practice: Build a marquee capability from the ground up with full ownership
- Work with the Best: Collaborate with top-tier talent and learn from industry leaders in AI
- Global Exposure: Be part of a high-growth firm operating across US, UK, UAE, India, and Singapore
- Continuous Growth: Access to certifications, tech events, and partner-led innovation labs
- Inclusive Culture: A supportive and diverse workplace that values learning, initiative, and ownership

Ready to build the future of AI with us?

- Apply now and become a part of a next-gen tech company that’s setting benchmarks in enterprise AI solutions.

📌 AI Tech Lead (Mumbai)
🏢 Exponentia.ai
📍 Mumbai