AI Engineer

Overview

Synechron is seeking an AI Engineer to build and implement AI agents and AI architecture within CI/CD workflows on AWS, developing AI-enabled solutions using LLMs, Generative AI, Python, RAG pipelines, MCP servers, vector databases, and AWS services.

What you'll do

• Build and implement AI agents and AI architecture within CI/CD workflows on AWS.
• Develop production-ready AI applications using LLMs and Generative AI platforms.
• Design, implement, and maintain RAG pipelines using SageMaker, Lambda, vector databases, embeddings, and retrieval components.
• Develop MCP servers and integrate approved tools, APIs, services, and enterprise data sources.
• Build agentic workflows and autonomous AI agents that support task planning, tool use, context management, and response validation.
• Use Python to develop scalable, maintainable, testable, and secure AI solutions.
• Support code generation and code fixing using LLMs, including code recommendations, defect identification, and remediation workflows.
• Integrate AI solutions with CI/CD workflows, source control, security tools, testing processes, and deployment pipelines.
• Use AWS services, including Lambda, ECS/EKS, S3, and API Gateway, to develop and operate AI applications.
• Apply application security principles to AI architecture, APIs, data flows, prompts, tools, model interactions, and generated code.
• Collaborate with software engineering, DevOps, security, architecture, and business stakeholders.
• Document AI architecture, data flows, system behavior, dependencies, security controls, and operational procedures.
• Support efficient use of models, compute, storage, and cloud resources to promote sustainable technology delivery.

What you'll need

• Hands-on experience with OpenAI, Bedrock, or similar LLM and GenAI platforms.
• Strong professional experience in Python and AI development, including application development, automation, API integration, testing, and deployment.
• Hands-on experience designing and implementing RAG pipelines using SageMaker and Lambda.
• Experience developing MCP servers and integrating tools, APIs, services, and data sources.
• Experience building agentic workflows or autonomous AI agents.
• Exposure to using LLMs for code generation, code analysis, code fixing, transformation, or remediation.
• Experience with vector databases, embeddings, similarity search, indexing, metadata filtering, and retrieval.
• Good knowledge of Lambda, ECS/EKS, S3, and API Gateway.
• Understanding of application security principles, common vulnerabilities, secure coding, access controls, and protection of AI applications and data.
• Minimum 8+ years of overall professional experience in software engineering, cloud engineering, AI engineering, data engineering, or related technology roles.
• Minimum 3+ years of AI experience, including hands-on work with LLMs, GenAI, Python, RAG pipelines, AI agents, or related AI application development.
• Demonstrated experience building and implementing AI agents and AI architecture within CI/CD workflows on AWS.
• Experience with RAG pipeline engineering using SageMaker, Lambda, vector databases, embeddings, and retrieval systems.
• Experience with MCP server development, tool integrations, agentic workflows, or autonomous AI agents.
• Experience applying application security principles to software, cloud, AI, API, and data solutions.
• Understanding of source control, branching, pull requests, code reviews, automated testing, and deployment practices.
• Understanding of prompt design, context management, response validation, and model evaluation.
• Understanding of secure coding, input validation, output validation, dependency management, and secrets protection.
• Understanding of authentication, authorization, identity and access management, and least-privilege controls.
• Ability to secure LLM applications, RAG pipelines, MCP servers, APIs, prompts, tools, and generated code.
• Awareness of risks such as prompt injection, data leakage, insecure tool execution, excessive permissions, malicious content, and untrusted model output.
• Experience applying security reviews, vulnerability assessments, and remediation practices to AI and software solutions.
• A bachelor's or master's degree in Computer Science, Information Technology, Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent relevant experience.

Nice to have

• Understanding and exposure to CI/CD tools such as GitHub, Jenkins, Harness, or equivalent tools.
• Understanding and exposure to security tools such as Snyk, SonarQube, or equivalent tools.
• Knowledge of containerization and orchestration using Docker and Kubernetes.
• Prior work in security automation or remediation systems.
• Experience with automated testing, vulnerability scanning, code quality checks, and deployment security gates.
• JavaScript or TypeScript experience for AI interfaces, service integrations, or tool development.
• Shell scripting experience for automation and CI/CD activities.
• Relational and NoSQL database experience.
• Experience with managed vector database services and hybrid search.
• Experience with AI agent orchestration frameworks.
• Experience with model evaluation, tracing, observability, prompt management, and response-quality measurement.
• AWS, AI, machine learning, cloud architecture, or application security certifications.

Details

• Location: Pune - Hinjewadi (Ascendas).