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 Skills





Business 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.

We are an Equal Opportunity Employer. TIAA does not discriminate against any candidate or employee on the basis of age race color national origin sex religion veteran status disability sexual orientation gender identity or any other legally protected status.

Our Culture of Impact

At TIAA were on a mission to build on our 100 year legacy of delivering for our clients while evolving to meet tomorrows 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 setting where teams work across organizational boundaries with shared purpose accelerating innovation and delivering meaningful results. Our workplace brings together TIAA and Nuveens entrepreneurial spirit where we work hard and work together to create lasting impact. Here every associate can grow through meaningful learning experiences and development pathwaysbecause when our people succeed our impact on clients lives grows stronger.

Accessibility Support

TIAA offers support for those who need assistance with our online application process to provide an equal employment opportunity to all job seekers including individuals with disabilities.

If you are a U.S. applicant and desire a reasonable accommodation to complete a job application please use one of the below options to contact our accessibility support team:

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Privacy Notices

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Required Experience:

Senior IC

📌 Senior Associate AI ML Engineer (Pune)
🏢 TIAA
📍 Pune