We’re Hiring: Consultant - Backend & Agentic AI Engineering at Chryselys
Location: Hyderabad
Job Type: Full-time
About Us:
Chryselys is a Pharma Analytics & Business consulting company that delivers data-driven insights leveraging AI-powered, cloud-native platforms to achieve high-impact transformations.
We specialize in digital technologies and advanced data science techniques that provide strategic and operational insights.
Who we are:
People - Our team of industry veterans, advisors and senior strategists have diverse backgrounds and have worked at top tier companies.
Quality - Our goal is to deliver the value of a big five consulting company without the big five cost.
Technology - Our solutions are Business centric built on cloud native technologies.
We are seeking an experienced Backend & Agentic AI Engineer with 7–9 years of backend engineering experience across Python and/or Node.js, including at least 2.5 years of hands-on experience building production-grade GenAI, RAG, semantic layer, and agentic AI systems. The ideal candidate can design, build, scale, observe, evaluate, and continuously improve AI-enabled platforms that operate reliably in enterprise environments.
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7–9 years of professional backend engineering experience, preferably building scalable APIs, services, data-intensive platforms, and distributed systems.
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Strong hands-on development experience in Python and/or Node.js.
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Minimum 2.5 years of practical experience in Agentic AI, Generative AI, RAG systems, semantic search, semantic layer design, or LLM-powered enterprise applications.
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Proven experience taking AI-enabled systems from concept to production, including reliability, security, monitoring, and performance considerations.
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Design, build, and scale backend systems that support GenAI, RAG, semantic layer, and agentic AI use cases.
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Develop robust services and APIs using Python and/or Node.js with strong attention to performance, maintainability, and production readiness.
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Build semantic layers that enable structured access to enterprise knowledge, business entities, metadata, and domain concepts.
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Implement RAG pipelines including document ingestion, chunking, embeddings, indexing, semantic search, hybrid retrieval, ranking, grounding, and response generation.
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Engineer agentic workflows involving planning, tool usage, orchestration, memory, task routing, and multi-step reasoning patterns.
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Define and implement guardrails for safety, security, prompt injection protection, hallucination reduction, policy compliance, and controlled tool execution.
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Build observability modules for AI systems, including tracing, logging, metrics, prompt/response monitoring, retrieval quality tracking, latency, cost, and failure analysis.
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Evaluate and improve system performance using offline and online evaluation methods, golden datasets, retrieval metrics, LLM quality metrics, feedback loops, and experimentation.
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Collaborate with product, data science, platform, and business stakeholders to translate complex requirements into scalable technical solutions.
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Languages: Python, Node.js, TypeScript/JavaScript.
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Backend Engineering: REST APIs, microservices, asynchronous processing, distributed systems, caching, queues, service reliability, and scalable system design.
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GenAI & Agentic AI: LLM integration, prompt engineering, tool calling, agent orchestration, multi-agent workflows, planning patterns, and AI workflow frameworks.
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RAG & Semantic Systems: embeddings, vector databases, semantic search, hybrid search, metadata filtering, re-ranking, knowledge retrieval, grounding, and semantic layer design.
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Cloud & Deployment: containerized services, CI/CD, cloud-native deployment patterns, secure API integration, and production monitoring.
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Observability & Evaluation: AI tracing, telemetry, evaluation datasets, retrieval precision/recall, hallucination tracking, response quality scoring, latency/cost optimization, and continuous improvement loops.
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Strong backend engineering foundation with proven ability to build scalable, secure, and maintainable systems.
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Hands-on implementation experience with semantic layers, RAG pipelines, and enterprise knowledge retrieval systems.
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Practical exposure to agentic engineering, including workflow orchestration, tool integration, and controlled autonomous execution.
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Ability to define guardrails and governance mechanisms for safe and compliant AI behavior.
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Ability to instrument AI systems with observability, diagnostics, monitoring, and feedback capture.
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Ability to evaluate AI system quality and improve retrieval accuracy, response relevance, latency, reliability, and cost efficiency.
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Experience with LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar orchestration frameworks.
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Experience with vector databases and search platforms such as Pinecone, Weaviate, Milvus, OpenSearch, Elasticsearch, pgvector, or similar technologies.
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Experience with cloud AI services, secure enterprise integrations, identity and access controls, and data privacy requirements.
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Exposure to healthcare, life sciences, pharma data, commercial analytics, or regulated enterprise environments.
How to Apply:
Ready to make an impact? Apply now by clicking [here] or visit our careers page at https://chryselys.com/chryselys-career
Please include your resume and a cover letter detailing why you’re the perfect fit for this role.
Equal Employment Opportunity:
Chryselys is proud to be an Equal Employment Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Connect with Us:
Follow us for updates and more opportunities: https://linkedin.com/company/chryselys/mycompany
Discover more about our team and culture: http://chryselys.com
