Senior Associate - AI - ML Engineer

TIAA; Pune District; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

TIAA Global Capabilities is seeking an AI Platform Lead Engineer-IN to design and scale Generative AI solutions for enterprise applications in Mumbai/Pune. You will own end-to-end AI system delivery, from RAG pipelines to production-grade observability and multi-modal integrations.

Role demands 9–15 years of experience in AI/ML, strong Python skills, and hands-on work with LangChain, vector databases, and LLM APIs.

Qualifications

• Proven hands-on experience building and deploying Generative AI solutions, including RAG pipelines, prompt engineering, and LLM fine-tuning using frameworks such as LangChain, LlamaIndex, or similar.
• Strong proficiency in Python and experience working with LLM APIs (OpenAI, Anthropic, Hugging Face) and vector databases such as Pinecone, Weaviate, or FAISS.
• Solid understanding of model evaluation methodologies, including benchmarking, A/B testing, hallucination detection, and production monitoring.
• Experience with fine-tuning techniques such as SFT, RLHF, LoRA, and QLoRA, and domain-specific customization.
• Demonstrated ability to design and deploy production-grade AI systems with robust observability, logging, and monitoring.

Responsibilities

• Design and implement end-to-end Generative AI solutions focusing on scalability, reliability, and production readiness.
• Build and maintain RAG pipelines by integrating vector databases with embedding models and LLMs.
• Develop prompting strategies, templates, and workflows to maximize accuracy and performance.
• Fine-tune foundation models using SFT, RLHF, LoRA, and QLoRA.
• Establish evaluation frameworks to measure accuracy, latency, cost, and drift with A/B testing.
• Implement observability, logging, tracing, and alerting for production models.
• Design and deploy AI agents using low-code and high-code approaches.
• Integrate NLP, computer vision, document intelligence, and traditional ML into multi-modal solutions.
• Stay abreast of evolving AI tools and models to enhance solution quality.
• Collaborate with product, engineering, and business stakeholders for scalable architectures.
• Contribute to best practices and internal standards for Generative AI development.

Skills

Generative AI

RAG pipelines

Prompt engineering

LLM fine-tuning

Python

LLM APIs

Vector databases

Observability

MLOps

Cloud platforms

Education

University degree preferred

Tools

LangChain

LlamaIndex

Pinecone

Weaviate

FAISS

Job description

AI Platform Lead Engineer-IN

The AI Platform Lead Engineer builds and maintains the systems that support AI and machine learning applications, working to ensure the systems are scalable, efficient, and reliable.

Key Responsibilities and Duties

• Deploy, manage and scale AI systems, as well as support model activity and deployment infrastructure in cloud environments
• Work with infrastructure and application development teams, data engineers, and model owners, to better integrate the AI applications into mainstream enterprise applications.
• Put into production the ML models keeping in mind the scalability, optimization, resource availability, and security for the AI solution.

Educational Requirements

• University (Degree) Preferred

Work Experience

• 5+ Years Required; 7+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level

8IC

Total experience required : Between 9 to 15 Years

Job location : Mumbai / Pune

Responsibilities

• Design and implement end-to-end Generative AI solutions that address complex business challenges, with a strong focus on scalability, reliability, and production readiness.
• Build and maintain Retrieval-Augmented Generation (RAG) pipelines by integrating vector databases such as Pinecone, Weaviate, and FAISS with embedding models and large language models (LLMs) to deliver context-aware, knowledge-grounded responses at scale.
• Develop and optimize prompting strategies, templates, and workflows that maximize LLM accuracy, consistency, and performance across diverse use cases and user scenarios.
• Customize and fine-tune foundation models using techniques such as supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and parameter-efficient methods including LoRA and QLoRA to meet domain-specific performance requirements.
• Establish and maintain rigorous model evaluation frameworks that measure accuracy, latency, cost-efficiency, hallucination rates, and task-specific metrics, conducting A/B testing and comparative analysis to drive informed model selection and configuration decisions.
• Implement comprehensive observability and monitoring systems — including logging, tracing, and alerting — to continuously track model behavior, prompt-response patterns, token consumption, error rates, and performance drift in production environments.
• Design and deploy production-grade AI agents leveraging both low-code platforms and custom high-code implementations, balancing flexibility, maintainability, and performance to meet evolving business needs.
• Integrate a broad range of AI and ML capabilities — including natural language processing, computer vision, document intelligence, and traditional machine learning models — to build holistic, multi-modal solutions that solve complex problems.
• Continuously evaluate the rapidly evolving AI landscape, proactively researching and adopting emerging models, frameworks, and tools to enhance solution quality and sustain competitive advantage.
• Collaborate cross-functionally with product, engineering, and business stakeholders to translate requirements into scalable AI architectures, ensuring alignment between technical solutions and organizational objectives.
• Contribute to the development of best practices, reusable components, and internal standards for Generative AI development, fostering a culture of innovation, quality, and responsible AI use across the organization.

Must-Have Skills

• Proven hands-on experience building and deploying Generative AI solutions, including RAG pipelines, prompt engineering, and LLM fine-tuning using frameworks such as LangChain, LlamaIndex, or simila
• Strong proficiency in Python and experience working with LLM APIs (OpenAI, Anthropic, Hugging Face) and vector databases such as Pinecone, Weaviate, or FAISS
• Solid understanding of model evaluation methodologies, including benchmarking, A/B testing, hallucination detection, and performance monitoring in production environments
• Experience with fine-tuning techniques such as SFT, RLHF, LoRA, and QLoRA, along with familiarity with parameter-efficient training approaches for domain-specific model customization
• Demonstrated ability to design and deploy production-grade AI systems with robust observability, logging, and monitoring capabilities ensuring reliability and performance at scale

Good-to-Have Skills

• Exposure to multi-modal AI capabilities including computer vision, document intelligence, or speech processing integrated within broader AI/ML pipelines
• Familiarity with low-code AI agent platforms (such as Microsoft Copilot Studio, Flowise, or similar) alongside the ability to build custom high-code agent implementations
• Experience working within cloud environments such as AWS, Azure, or GCP, leveraging managed AI/ML services for model training, deployment, and scaling
• Knowledge of responsible AI principles, including bias detection, fairness evaluation, and compliance considerations relevant to regulated industries such as financial services
• Familiarity with MLOps practices and tools such as MLflow, Weights & Biases, or similar platforms for experiment tracking, model versioning, and deployment automation

Related SkillsBusiness Acumen, Data Preprocessing, Data Science, Innovation, Machine Learning, Market/Industry Dynamics, Predictive Modeling, Programming, Statistics

Company Overview

TIAA Global Capabilities was established in 2016 with a mission to tap into a vast pool of talent, reduce risk by insourcing key platforms and processes, as well as contribute to innovation with a focus on enhancing our technology stack. TIAA Global Capabilities is focused on building a scalable and sustainable organization , with a focus on technology , operations and expanding into the shared services business space.

Working closely with our U.S. colleagues and other partners, our goal is to reduce risk, improve the efficiency of our technology and processes and develop innovative ideas to increase throughput and productivity.

Our Culture of Impact

At TIAA, we're on a mission to build on our 100+ year legacy of delivering for our clients while evolving to meet tomorrow's challenges. We equip our associates with future-focused skills and AI tools that enable us to advance our mission. Together, we are fighting to ensure a more secure financial future for all and for generations to come. We are guided by our values: Champion Our People, Be Client Obsessed, Lead with Integrity, Own It, and Win As One. They influence every decision we make and how we work together to serve our clients every day. We thrive in a collaborative in-office environment where teams work across organizational boundaries with shared purpose, accelerating innovation and delivering meaningful results. Our workplace brings together TIAA and Nuveen's entrepreneurial spirit, where we work hard and work together to create lasting impact. Here, every associate can grow through meaningful learning experiences and development pathways—because when our people succeed, our impact on clients' lives grows stronger.

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