About The Role

CloudiQS is building an agentic AI capability that sits within a real product, interacts with real systems, and must behave predictably in production. This role is for a strong software engineer who wants to work on AI systems without sacrificing engineering discipline.

You’ll be building and owning AgentCore / Bedrock-based agents that can reason over CloudiQS data, call internal APIs safely, and produce outputs users can trust, with guardrails, observability, and clear failure modes.

Platform Engineering

• Architect Front End / Backend Integrations and deliver the agent runtime on AWS (Bedrock AgentCore, Lambda, Step Functions, CDK)
• Design the deployment pipeline: click deploy, sdk, config → provision → deploy → monitor, targeting rapid delivery
• Build multi-tenant infrastructure patterns that isolate customer workloads safely
• Own CI/CD, infrastructure-as-code, and automated testing

Agent Engineering

• Build AgentCore-based agents with tool use, memory, and retrieval (RAG) capabilities
• Implement guardrails: input/output validation, cost controls, permission boundaries, and circuit breakers
• Design observability: structured logging, trace capture, token tracking, and drift detection
• Define and enforce clear failure modes — agents must fail predictably, not silently

Team & Delivery

∙ Set engineering standards: code review, testing strategy, incident response, documentation

∙ building with production milestones, not research sprints

∙ Work directly with the team to translate customer requirements into engineering priorities

What We are Looking For

Must Have

∙ 5+ years of software engineering experience, at least 2 years in a senior or lead role

∙ Strong Python and/or TypeScript in production environments

∙ Hands-on AWS: Lambda, Step Functions, CDK/CloudFormation, IAM, and familiarity with Bedrock

∙ Experience building systems that call external APIs with retry logic, rate limiting, and graceful degradation

∙ Track record of shipping and operating production services — not just prototypes

∙ Comfortable making architectural decisions with incomplete information

∙ Experience hiring engineers and setting technical direction for a small team

Strong Preference

• Experience with LLM-based systems: prompt engineering, tool use patterns, RAG pipelines, or agent frameworks
• AWS certifications (Solutions Architect, Developer, or DevOps Engineer)
• Background in multi-tenant SaaS or platform engineering
• Observability tooling experience (CloudWatch, Datadog, OpenTelemetry)

What We Don’t Need

• A pure ML researcher, we use foundation models via Bedrock, not custom training
• A manager who doesn't write code is hands-on, especially in Year 1
• Someone who needs a mature platform to be productive — you will be building it

Why CloudiQS

• ∙ Greenfield build — you’re setting the foundation, not inheriting debt
• ∙ Direct impact — your work ships to customers within weeks, not quarters
• ∙ AWS Advanced Tier partners with GenAI, Migration, and Microsoft Workloads competencies

∙ Equity participation in the platform you build

Job Type: Full-time

Pay: ₹1,400,000.00 - ₹2,200,000.00 per year

Benefits:

• Work from home

Experience:

• AWS Services : 5 years (Required)
• Ai and ML: 3 years (Required)
• Build automation: 4 years (Required)
• React: 3 years (Required)
• Node.js: 3 years (Required)
• Full-stack development with AWS background : 5 years (Required)

Work Location: Remote