How You'll Help Us Keep Climbing (Overview &

- Key Responsibilities)

Role Summary

We are seeking a highly skilled Sr AI ML Engineer to design, build, and scale enterprise-grade AI applications on AWS. This role is responsible for developing AI-powered products using Amazon Bedrock, AgentCore, foundation models, Retrieval-Augmented Generation (RAG), agentic AI, and serverless AWS technologies.

The role will lead the full AI engineering lifecycle, from use-case discovery and solution architecture through development, evaluation, deployment, monitoring, and ongoing optimisation. The ideal candidate combines strong software engineering skills with expertise in generative AI, agent orchestration, enterprise integration, security, governance, and cloud-native architecture.

Key Responsibilities

AI Application Development

- Design, build, and deploy production-ready AI applications using Amazon Bedrock and supported foundation models.
- Develop AI-powered copilots, knowledge assistants, document intelligence solutions, and intelligent workflow automation.
- Implement prompt engineering, structured outputs, tool calling, context management, and model integration patterns.
- Build reusable AI services, frameworks, and accelerators that support multiple enterprise use cases.
- Develop secure APIs and backend services using Python, FastAPI, AWS Lambda, and API Gateway.

Agentic AI &
- AgentCore

- Design and develop intelligent agents using Amazon Bedrock AgentCore and related AWS capabilities.
- Build multi-agent solutions using coordinator-worker, planner-executor, and human-in-the-loop patterns.
- Implement agent runtime, memory, identity, gateway, observability, browser, and code interpreter capabilities where appropriate.
- Enable agents to reason, plan, invoke tools, access approved data sources, and execute controlled business workflows.
- Integrate agents with enterprise applications, APIs, databases, and tools using Model Context Protocol (MCP) and other approved integration patterns.

RAG &
- Enterprise Knowledge Systems

- Design and implement RAG architectures using Bedrock Knowledge Bases, embeddings, vector search, and semantic retrieval.
- Build enterprise knowledge assistants that use structured and unstructured data such as policies, reports, contracts, and operational datasets.
- Optimise document ingestion, chunking, metadata, retrieval, reranking, grounding, and context assembly.
- Improve response quality through retrieval evaluation, citation support, relevance testing, and hallucination reduction techniques.
- Connect AI applications securely to Amazon S3, Redshift, OpenSearch, DynamoDB, and approved enterprise data sources.

AWS AI Platform Engineering
- Architect scalable, resilient, and cost-efficient AI solutions using AWS serverless and managed services.
- Build orchestration workflows using AWS Lambda, Step Functions, EventBridge, API Gateway, and container services where required.
- Implement AI observability, request tracing, usage metrics, logging, alerting, and operational dashboards using CloudWatch and AgentCore capabilities.
- Establish CI/CD pipelines, Infrastructure as Code, automated testing, prompt versioning, and environment promotion practices.
- Optimise model selection, inference configuration, latency, throughput, token usage, and overall platform cost.

Responsible AI, Security &
- Governance





- Implement Amazon Bedrock Guardrails and approved runtime controls for prompts and model responses.
- Address risks such as prompt injection, data leakage, hallucinations, unsafe outputs, excessive agency, and unauthorised tool usage.
- Apply IAM least privilege, encryption, secrets management, network security, audit logging, and data protection standards.
- Build evaluation frameworks to measure accuracy, groundedness, relevance, safety, latency, reliability, and cost.
- Ensure AI solutions comply with enterprise architecture, security, privacy, risk, and responsible AI requirements.

Technical Leadership &
- Collaboration

- Define AWS AI engineering standards, reference architectures, reusable patterns, and development best practices.
- Lead solution design, architecture reviews, code reviews, testing reviews, and production readiness assessments.
- Mentor AI engineers and software engineers in Bedrock, AgentCore, RAG, agentic AI, and cloud-native development.
- Partner with product owners, data engineers, security teams, architects, and business stakeholders to identify and prioritise high-value AI opportunities.
- Translate business needs into scalable AI products with clear success measures and measurable business outcomes.

What You Need To Succeed (Minimum Qualifications)

- Bachelor's degree in Computer Science, Artificial Intelligence, Engineering, Data Science, Information Systems, or a related field.
- 4+ years of experience in software engineering, cloud engineering, machine learning engineering, or AI application development.
- 3+ years of experience leading technical teams, architecture initiatives, or complex solution delivery.
- Hands-on experience building generative AI or LLM-based applications on AWS.
- Strong experience with Amazon Bedrock, foundation model APIs, prompt engineering, and tool integration.
- Experience designing RAG solutions, enterprise knowledge applications, or semantic search systems.
- Strong programming experience in Python and experience building REST APIs and microservices.
- Experience designing secure, scalable, and observable cloud-native applications on AWS.
- Solid understanding of software engineering practices, automated testing, CI/CD, and Infrastructure as Code.
- Excellent communication, technical leadership, problem-solving, and stakeholder engagement skills.

What Will Give You a Competitive Edge (Preferred Qualifications)

- Experience with Amazon Bedrock AgentCore, Bedrock Agents, Knowledge Bases, and Guardrails.
- Experience with agent frameworks such as Strands Agents, LangGraph, CrewAI, or LangChain.
- Experience implementing MCP-based tool and system integrations.
- Experience with vector databases, embeddings, reranking, document processing, and multimodal AI.
- Experience with AI evaluation, red teaming, model monitoring, prompt management, and responsible AI controls.
- Experience deploying AI solutions in regulated or security-sensitive enterprise environments.




- Experience building AI solutions for Finance, analytics, document automation, or decision-support use cases.
- Relevant AWS AI, Machine Learning, Developer, or Solutions Architect certification.

About The Company What started as a humble, little aerial crop-dusting operation called Huff Daland Dusters in 1924 has now grown into the U.S. global airline leader in safety, innovation, reliability, and customer experience. Headquartered in Atlanta, Georgia, Delta Air Lines is known for its operational excellence and award-winning customer service. Powered by our employees worldwide, Delta has led the airline industry in operational excellence for a decade while maintaining our reputation for award-winning customer service. With our mission of connecting the people and cultures of the globe, Delta strives to foster understanding across a diverse world and serve as a force for social good.

In 2026, Delta Air Lines continued to earn global recognition for its performance, culture and operational excellence. Delta was named Glassdoor’s 2026 Top 100 Best Places to Work list for the ninth time, standing as the only airline recognized. Delta also secured the 11th spot on Fortune’s World’s Most Admired Companies list, marking its 13th consecutive year earning this distinction.

Delta was also recognized by Cirium as the top on-time airline in North America for the fifth consecutive year, underscoring its unwavering commitment to reliability and customer experience.

About The Delta Technology Hub (DTH), Bangalore The DTH is one of Delta Air Lines' investments in world-class business capabilities and technology aimed at transforming how Delta Air Lines operates and provides world-class travel experiences to its customers through innovation and cutting-edge methodologies. By continuously reimagining processes and driving technology-led transformation, the Delta Technology Hub plays a pivotal role in Scripting The Future Of Aviation. The organization is certified by the Great Place to Work Institute (India).

The Delta Technology

Hub was a finalist for the iVolunteer Awards 2024/2025 in the "Leader in Employee Volunteering" category. This nomination highlights our remarkable volunteering initiatives and the outstanding practices we implement to encourage and support our employee volunteering program.

For more information, please visit www.deltatechhub.com

Why join?

- Technology is a key enabler of the differentiated services that Delta provides. At the DTH, you get the opportunity to work on projects with a significant impact on business outcomes and customer experience.
- Deepen your knowledge by taking part in multifaceted learning and development programs –exposure to extensive internal and partner repositories, institutional affiliations, and industry SIG (Special Interest Groups) partnerships.
- Immerse yourself in an employee-centric culture.
- Develop deep and broad business acumen on airline operations while retaining focus on cutting-edge technology driven solutions.
- Avail a full range of benefits that support you and your family: Medical Insurance, Transportation to and from the DTH office, Complementary Cafeteria Meals, Special Travel opportunities and Travel Privileges, Car Lease Program, Paid time off, Parental Benefits and National Pension Scheme.

📌 Senior AI/ML Engineer (Bengaluru)
🏢 Delta Technology Hub
📍 Bengaluru