INDStaff Software Engineer - AI

The Hartford India; Hyderabad; On-site; INR 3,500,000 - 7,500,000; Full time

Job summary

The Hartford India is seeking a highly skilled T7 AI Engineer to join our Hyderabad engineering team. This full-time role blends hands-on AI/ML engineering with scalable software development to design, deploy, and operate production-grade AI systems across enterprise applications.

Responsibilities include building AI-powered solutions, integrating LLM APIs (GCP Vertex AI), and developing AI orchestration workflows using LangChain, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex.

Qualifications

• 8+ years of professional software engineering experience with 2+ years in AI/ML solution development and delivery.
• Bachelor's degree in Computer Science, Software Engineering, AI/ML, or related field (or equivalent experience).
• Strong understanding of LLM architectures, capabilities, and limitations.
• Proficiency with AI orchestration frameworks and major LLM providers (OpenAI, Vertex AI, AWS Bedrock).
• Expert-level Python; strong skills in at least one additional language (Java, TypeScript/Node.js, C#/.NET).

Responsibilities

• Design, build, and deploy production AI systems including RAG pipelines and agentic workflows.
• Integrate LLM APIs and AI services into enterprise applications (GCP Vertex AI).
• Implement prompt engineering, fine-tuning, embeddings, and vector search solutions.
• Build AI orchestration workflows using LangChain, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex.
• Develop AI agents, tools, and autonomous workflows to solve business problems.
• Establish evaluation frameworks for AI systems measuring accuracy, latency, cost, and outcomes.
• Build end-to-end AI-powered applications spanning frontend, backend, APIs, and data layers.
• Develop robust backend services with Python (FastAPI/Django) or Node.js.
• Implement and optimize RESTful APIs, GraphQL endpoints, and event-driven integrations.
• Build modern frontends for AI features using React, Angular, or Vue.js with TypeScript.
• Maintain production-ready code with focus on maintainability and operations.
• Design MLOps/LLMOps pipelines for reliable deployment and lifecycle management.
• Configure cloud-native AI infrastructure (AWS, GCP) including model serving and auto-scaling.
• Build CI/CD for AI model deployment, testing, and evaluation.
• Implement observability for AI systems including monitoring drift, costs, latency.
• Provide training and mentorship on AI tools and patterns; contribute to knowledge bases.

Skills

AI/ML engineering

Software engineering

Python

TypeScript/Node.js

C#/.NET

Education

Bachelor's degree in Computer Science or related field

Tools

LangChain

Semantic Kernel

AutoGen

CrewAI

LlamaIndex

Docker

Kubernetes

Jenkins

GitHub Actions

Job description

IND Staff Software Engineer - GCC011

We’re determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.

Position Summary

We are seeking a highly skilled T7 AI Engineer to join our engineering team in Hyderabad, India. This role combines hands-on AI/ML engineering with deep software development expertise to build, deploy, and operate production-grade AI systems at enterprise scale. You will design and implement AI-powered solutions - from LLM integrations and agentic workflows to ML pipelines and intelligent automation - while driving AI adoption and engineering excellence across teams.

Level: T7 (Senior Engineer)

Location: Hyderabad, India

Employment Type: Full-Time

Key Responsibilities

AI/ML Engineering & Delivery

• Design, build, and deploy production AI systems including RAG pipelines, agentic workflows, multi-model orchestration, and intelligent automation


• Integrate large language model (LLM) APIs and AI/ML services into enterprise applications (GCP Vertex AI)


• Implement and optimize prompt engineering strategies, fine-tuning pipelines, embeddings, and vector search solutions


• Build and maintain AI orchestration workflows using frameworks such as LangChain, Semantic Kernel, AutoGen, CrewAI, or LlamaIndex


• Develop custom AI agents, tools, and autonomous workflows that solve real business problems


• Establish evaluation frameworks for AI systems - measuring accuracy, latency, cost, hallucination rates, and business outcomes

Full Stack Development & Integration

• Build end-to-end AI-powered applications spanning frontend, backend, APIs, and data layers


• Develop robust backend services using Python (FastAPI/Django) or Node.js to support AI workloads


• Implement and optimize RESTful APIs, GraphQL endpoints, and event-driven integrations for AI services


• Build modern frontend interfaces for AI-powered features using React, Angular, or Vue.js with TypeScript


• Write clean, well-tested, production-ready code with a focus on maintainability and operational excellence

MLOps & AI Infrastructure

• Design and implement MLOps/LLMOps pipelines for reliable model deployment, versioning, and lifecycle management


• Configure and manage cloud-native AI infrastructure (AWS, GCP) including model serving, orchestration, and auto-scaling


• Implement observability for AI systems - monitoring model drift, token costs, latency, throughput, and quality metrics


• Build and maintain CI/CD pipelines for AI model deployment, automated testing, and continuous evaluation


• Design for resilience: failover strategies, fallback models, circuit breakers, and graceful degradation

AI-Augmented Development

• Leverage AI coding assistants (GitHub Copilot, Cursor, Claude, etc.) to dramatically accelerate development workflows


• Use AI tools for code generation, refactoring, test writing, documentation, and code review


• Develop and maintain custom AI-powered developer tools, automations, and internal platforms


• Establish guardrails, security practices, and governance for responsible AI usage in engineering

Technical Documentation & Mentorship

• Influence engineering culture by evangelizing AI-first development practices across teams


• Train and upskill team members on effective use of AI tools, LLM integration patterns, and ML best practices


• Contribute to internal knowledge bases, tech talks, and communities of practice


• Partner with product, design, and data science teams to identify and deliver AI-driven opportunities


• Participate in architecture reviews and design discussions, ensuring AI solutions are production-ready from day one

Required Qualifications

• Experience: 8+ years of professional software engineering experience, with 2+ years focused on AI/ML solution development and delivery


• Education: Bachelor's degree in Computer Science, Software Engineering, AI/ML, or related field (or equivalent experience)


• AI/ML Expertise:




• Strong understanding of large language model architectures, capabilities, and limitations


• Proven track record building and deploying production AI systems (RAG, agents, fine-tuning, embeddings, vector search)


• Proficiency with AI orchestration frameworks (LangChain, Semantic Kernel, AutoGen, CrewAI, LlamaIndex)


• Hands-on experience with major LLM providers and platforms (OpenAI, Anthropic, Google Vertex AI, AWS Bedrock)


• Solid understanding of prompt engineering, evaluation methodologies, and AI safety/guardrails




• Programming: Expert-level proficiency in Python; strong skills in at least one additional language (Java, TypeScript/Node.js, C#/.NET)


• Cloud & Infrastructure: Hands-on experience deploying and operating AI workloads on cloud platforms (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD tooling (Jenkins, GitHub Actions)


• Data: Proficiency with SQL and NoSQL databases, vector databases (Pinecone, Weaviate, pgvector, ChromaDB), and data pipeline tools


• API Development: Proven track record building production APIs (REST, GraphQL, gRPC) and event-driven integrations


• AI Tools Proficiency: Advanced daily usage of AI coding assistants with demonstrated impact on productivity and code quality


• Testing: Strong testing practices for AI systems including model evaluation, integration testing, and automated quality checks


• Communication: Excellent written and verbal communication skills with ability to explain complex AI concepts to diverse audiences

Preferred Qualifications

• Experience building enterprise AI platforms serving multiple product teams


• Familiarity with custom model training, fine-tuning (LoRA, QLoRA), and RLHF techniques


• Experience with agent-based AI architectures and autonomous multi-step workflows


• Knowledge of AI security concerns (prompt injection, data leakage, model poisoning) and mitigation strategies


• Experience in regulated industries (insurance, finance, healthcare) with security and compliance requirements


• Contributions to open-source AI/ML projects or published technical content


• Cloud certifications (AWS Solutions Architect, GCP Professional Cloud Architect, or equivalent)


• Experience with real-time inference, streaming responses, and low-latency AI serving architectures