Applied Systems India Private Limited · KA, India
Skills: React, Python, AWS, Docker, CI/CD
External Job Ad:
AI Engineer / Software Engineer
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Applied Systems, Inc., a worldwide leader in insurance technology, is currently searching for a Data Migration Manager to lead a team within our Data Services organization. This role is responsible for the people leadership, delivery oversight, and client-facing communication needed to ensure that customer data migrations from competitor and legacy systems into Applied Systems SaaS products are executed seamlessly, on time, and with a high standard of quality and customer satisfaction.
Job Summary
In this role, you will design, build, and deploy Generative AI solutions—LLM-powered applications, retrieval-augmented generation (RAG), and agentic workflows—integrated with enterprise data and systems. Working alongside senior engineers and in close collaboration with product, engineering, and security partners, you’ll help deliver reliable, scalable, and safe GenAI capabilities, with a focus on evaluation, observability, and cost/latency performance in production.
What You’ll Do
Design and implement LLM-powered conversational experiences (chat assistants/AI Agents), integrating tools, APIs, and enterprise data sources
Build and maintain RAG pipelines (document ingestion, chunking, embeddings, indexing) using vector databases and AI-enabled search
Develop LLM inference and orchestration components (prompt templates, function/tool calling, streaming, caching) that meet defined latency and reliability targets
Implement safety and compliance guardrails (content filtering, prompt injection defenses, data access controls) and support red-teaming/testing of GenAI applications
Help optimize GenAI solutions for cost and performance (token usage, prompt compression, caching, model routing) while maintaining response quality
Apply Responsible AI practices for GenAI (grounding, hallucination mitigation, privacy-by-design, bias/toxicity evaluation) and align with s …truncated… th vector databases and retrieval s…
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