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AI Engineer – Python, LLM/GenAI, RAG, AWS & AI Agents
Synechron (company site, opens in a new tab)8+ yrsPuneOn-siteDirect career pageEst. 20–40 LPA
Posted 11h ago
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Job description
Structured overview of role & requirements
About This Role
- Design, develop, and implement AI agents, RAG pipelines, MCP servers, and AI architecture within AWS-based CI/CD workflows.
- Build and maintain production-ready generative AI solutions using Python, large language models (LLMs), AWS services, and vector databases with a focus on scalability, security, and operational stability.
- Drive measurable improvements in developer productivity through code generation, fixing, security automation, and integrate AI solutions with source control and security tools.
Minimum Requirements
- Minimum 8+ years overall professional experience in software, cloud, AI, or related engineering roles with at least 3+ years hands-on AI experience involving LLMs, GenAI, RAG pipelines, AI agents.
- Strong professional experience in Python programming and AI development including API design, automation, testing, and production deployment.
- Hands-on experience with AWS services including Lambda, ECS/EKS, S3, API Gateway, SageMaker in deploying and operating AI applications integrated into CI/CD workflows.
- Demonstrated expertise in designing and implementing RAG pipelines, autonomous AI agents and MCP servers, application security principles for AI and cloud applications.
Ideal Candidate Profile
- Experienced AI engineer with deep technical competency in LLMs, RAG pipelines, agentic AI workflows integrated into AWS cloud infrastructure and CI/CD environments.
- Skilled in secure AI architecture design emphasizing operational reliability, cost optimization, and adherence to security best practices within AI and cloud ecosystems.
- Able to collaborate cross-functionally with DevOps, security, engineering, and business stakeholders to deliver enterprise-grade AI solutions and document AI systems comprehensively.