INDStaff Software Engineer - AI

Job Details

Location:

Hyderabad, Telangāna, IN

Category:

Information Technology

Employment Type:

Full time

Job Ref:

R2626213-333

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