INDStaff Software Engineer - AI

• *Job Details**
• --------------

Location

Hyderabad, Telangāna, IN

Category

Information Technology

Employment Type

Full time

Job Ref

R2626217\-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**