Sr. AWS Developer, Products

Accountabilities • Build core AI product capabilities, including conversation ingestion, topic detection, LLM-based evaluations and scoring, personally identifiable information (PII) redaction, and insights and recommendations.

• Develop generative AI solutions using Amazon Bedrock, including model invocation, agents, AgentCore, Knowledge Bases, retrieval-augmented generation (RAG), guardrails, and third-party LLM APIs.

• Design and implement Model Context Protocol (MCP) servers and agentic interfaces that enable AI assistants and customer tools to access product data and actions.

• Build AI agent observability capabilities, including session and trace capture, evaluation frameworks, quality scoring, and production health metrics.

• Develop and maintain serverless backend services using AWS Lambda, API Gateway, DynamoDB, Aurora/RDS, S3, Kinesis, and Step Functions.

• Own infrastructure as code using AWS CDK, creating reusable, secure, and hardened components that can be deployed into customer-owned AWS accounts.

• Build and maintain Amazon Connect integrations involving Contact Trace Records (CTR), Contact Lens, agent event streams, Lex bots, and contact flows.

• Strengthen application security through Cognito/OIDC authentication, least-privilege IAM policies, encryption, and remediation of findings from security testing and assessments.

• Lead code reviews, mentor other developers, and take end-to-end technical ownership of product initiatives with minimal supervision.

Requirements:

• At least 5 years of professional software development experience.

• Strong hands-on programming skills in Python and/or TypeScript/Node.js.

• Practical experience engineering generative AI and LLM applications, including prompt design, RAG, structured outputs, LLM-as-judge evaluations, guardrails, and token and cost optimization.

• Production experience with Amazon Bedrock or equivalent LLM platforms.

• Strong knowledge of AWS serverless architecture, including Lambda, API Gateway, DynamoDB, S3, and EventBridge/Kinesis.

• Experience with AWS CDK or CloudFormation, infrastructure as code, and CI/CD pipelines.

• Hands-on Amazon Connect experience, including contact flows, Lex, and CTR/Contact Lens data streams.

• Experience building AI agents with Amazon Connect, Lex, and Bedrock for voice or chat self-service and agent assistance.

• Proven ability to build and operate REST APIs and event-driven integrations across multiple systems.

• A security-focused development approach, including IAM, Cognito, KMS encryption, VPC and network design, and secure software development practices.

• AWS Developer or Solutions Architect certification at the Associate or Professional level.

• Strong problem-solving, communication, collaboration, and technical leadership skills.

• Preferred qualifications: Experience developing MCP servers or using agentic frameworks such as Bedrock AgentCore, LangGraph, Strands, or CrewAI; AI agent evaluation and observability; multi-tenant SaaS or products deployed into customer cloud accounts; broader contact center technologies, including workforce management and WebRTC/SIP; familiarity with Salesforce Service Cloud, Data Cloud, or Agentforce; and AWS AI Practitioner or Machine Learning Specialty certification.

Benefits:

• Remote work within India, limited to the listed eligible locations: Bengaluru, Chennai, Gurugram, Hyderabad, Noida, or Pune.

• Flexible working arrangements built around trust, personal responsibilities, and outcomes rather than rigid working hours.

• A collaborative environment that encourages employees to contribute ideas and feedback through team discussions, town halls, and company meetings.

• Opportunities to work with emerging AI, generative AI, AWS, and contact center technologies.

• A team culture that values connection, recognition, and celebrating achievements together.

• Travel may be required for certain roles, with an anticipated commitment of up to 25%; the specific travel expectations for this position are not confirmed.

• Salary, healthcare coverage, and other financial or insurance benefits are not specified in the job description.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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