Job Description:

About Us

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.
One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We're devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.
Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Global Business Services

Global Business Services delivers Technology and Operations capabilities to Lines of Business and Staff Support Functions of Bank of America through a centrally managed, globally integrated delivery model and globally resilient operations.
Global Business Services is recognized for flawless execution, sound risk management, operational resiliency, operational excellence and innovation.
In India, we are present in five locations and operate as BA Continuum India Private Limited (BACI), a non-banking subsidiary of Bank of America Corporation and the operating company for India operations of Global Business Services.

Process Overview

As part of Global Markets Technology Strategy & Innovation, working closely with the Quantitative Strategies & Data Group (QSDG) and Platform teams, this organization is chartered with driving the firm's AI-first transformation across trading, research, and client engagement.

Our mission is to build enterprise-grade GenAI capabilities that unlock new insights from structured and unstructured data, accelerate revenue growth, and enhance operational efficiency across Global Markets. We are building a platform that serves a rapidly growing pipeline of GenAI use cases, leveraging both proprietary and open-source Large Language Models (LLMs) alongside the firm's vast data assets.

Job Description

Generative AI (GenAI) presents a transformational opportunity to derive deeper insights from data, accelerate revenue growth, and enhance business processes. We are seeking a Senior Software Engineer to design, build, and deploy production-grade GenAI solutions on our Global Markets platform.

As a Senior Software Engineer, you will be hands-on building RAG pipelines, integrating LLMs, developing model serving infrastructure, and implementing MLOps workflows. You will work across the full stack-from data ingestion and embeddings to model deployment and monitoring-delivering AI-powered capabilities that directly impact traders, researchers, and clients.

This role requires strong software engineering fundamentals combined with deep expertise in GenAI technologies. You will collaborate with cross-functional teams, mentor junior engineers, and drive innovation through rapid prototyping and production delivery.

Responsibilities:-

GenAI Development & Implementation

Design and implement end-to-end Retrieval-Augmented Generation (RAG) pipelines including document processing, embedding generation, vector storage, and retrieval optimization
Build and deploy LLM-based applications using frameworks like LangChain, LlamaIndex, or Haystack
Develop prompt engineering workflows, template libraries, and prompt optimization strategies for enterprise use cases
Implement fine-tuning pipelines using LoRA, QLoRA, Adapters, or instruction tuning methodologies
Build agent-based architectures with tool augmentation and multi-step reasoning capabilities
Integrate multimodal models handling text, tabular data, and unstructured content

Platform & Infrastructure

Develop production-grade model serving infrastructure using Docker, Kubernetes/OpenShift, and model frameworks
Build scalable inference APIs with load balancing, caching, and request routing
Implement vector database solutions with optimized indexing and search
Design and deploy microservices for data preprocessing, feature extraction, and post-processing
Optimize model inference performance through quantization, batching, and hardware acceleration

MLOps & Model Lifecycle

Build CI/CD pipelines for model deployment, versioning, and rollback
Implement model monitoring, drift detection, and automated evaluation frameworks
Develop A/B testing infrastructure for model comparison and champion/challenger strategies
Create logging and observability solutions for LLM requests, responses, and performance metrics
Build hallucination detection, factuality checks, and safety guardrails into production pipelines

Collaboration & Delivery

Partner with business stakeholders, quants, and product managers to translate requirements into technical solutions
Conduct code reviews and provide technical mentorship to junior engineers
Participate in architecture discussions and contribute to platform design decisions
Drive agile delivery with sprint planning, estimation, and on-time execution
Document technical designs, APIs, and operational runbooks

Innovation & Quality

Research and prototype emerging GenAI technologies and techniques
Conduct performance benchmarking and optimization of AI workloads
Implement comprehensive testing strategies including unit, integration, and evaluation tests
Address security, compliance, and data privacy requirements across AI workflows
Stay current with advances in LLMs, embeddings, vector search, and AI infrastructure

GenAI-Specific Skills Required

Strong hands-on experience with LLM frameworks (Hugging Face Transformers, PyTorch, TensorFlow)
Proven experience building and deploying RAG systems with vector databases
Expert-level Python programming with experience in AI/ML libraries (LangChain, FAISS, sentence-transformers)
Hands-on prompt engineering and building production prompt templates
Experience deploying and scaling GenAI workloads in containerized environments
Knowledge of LLM evaluation techniques (BLEU, ROUGE, BERTScore, human evaluation)
Understanding of LLM safety frameworks, bias detection, and guardrail implementation
Experience with embedding models and semantic search optimization

Requirements

Education- Bachelor's or master's degree in computer science, Engineering, or equivalent experience

Certifications if any- NA

Experience Range- 06-10+ Years

Foundational skills

Software engineering experience with strong full-stack capabilities
Experience in building and deploying AI/ML solutions in production environments
Expert-level Python programming and Unix/Linux scripting
Experience with modern software engineering practices (Git, CI/CD, testing frameworks, code quality tools)
Strong knowledge of relational databases (Oracle, MySQL, Impala) and NoSQL systems (MongoDB, Redis)
Experience with front-end technologies (HTML/CSS, JavaScript, React) and RESTful API development
Proficiency with cloud platforms and container orchestration (Kubernetes, Docker)
Strong problem-solving skills and ability to debug complex distributed systems
Excellent communication skills for technical and business audiences

Desired skills:-

Experience implementing AI solutions in financial services or regulated environments
Knowledge of LLM fine-tuning, model compression, or inference optimization
Hands-on experience with agent frameworks and tool-augmented LLMs
Exposure to Global Markets (Sales & Trading) workflows and financial data
Experience with real-time data processing and streaming architectures (Kafka)
Contributions to open-source AI/ML projects

Work Timings- 11 AM to 8.00 PM

Job Location- Chennai / Mumbai