Senior Software Engineer

Build the AI agents, sync engine, and full-stack product that keep enterprise CRMs and cloud partner programs in lockstep, and own them in production. Title : Senior Software Engineer (Cloud & AI) Experience : 5+ years of professional software engineering. Core stack : Python, TypeScript/React, Go, AWS, GCP, Azure, LLMs Location : Bengaluru, India (in-office) Employment type : Full-time About Labra Labra builds cloud-native B2B SaaS products powered by AI agents that help companies accelerate their cloud transformation. Our teams work at the intersection of generative AI, AI agents, cloud infrastructure, and modern full-stack engineering, shipping products that customers and internal teams use every day. The Role This is a hands-on role with real scope across three areas: AI agents and LLM features, the backend and sync engine, and the React product customers use. Your depth can be in one area, as long as you're comfortable working across all three. You'll join a pod that pairs feature work with stability work. You'll take problems from a half-formed customer need to architecting a feature running reliably in production: designing the system, writing most of the code, reviewing teammates' work, and being accountable for how it behaves once it ships. What You'll Own 1. AI agents and LLM features 2. Build production AI agents and LLM features with RAG, tool calling, and MCP-based workflows. 3. Design context management: memory, compression, retrieval and prompt optimization. 4.Optimize for time to first token (TTFT), latency, token usage, and cost through caching, parallel tool execution, and reducing unnecessary LLM calls. 5.Ship streaming AI experiences over SSE and WebSockets. Sync engine and integrations 1.Design, build and ship modules for various business systems’ (such as CRM, ERPs) integrations, sync configuration and co-sell pipeline visibility. 2.Make high-volume, bidirectional sync between CRMs and cloud partner programs fast, correct and recoverable. 3.Build event-driven processing on AWS SQS, EventBridge, SNS, Lambda, and Step Functions, with robust retries, idempotency, and dead-letter handling. Full-stack product 1.Build customer-facing features in React and TypeScript, backed by well-designed REST APIs and services in Python or Go. 2.Implement authentication, authorization, RBAC, and secure third-party integrations. 3.Profile slow endpoints and queries, tune connection pools and aggregation pipelines, and load-test before customers hit the limits. 4.Write automation and unit tests for the code before it is deployed. Production and engineering quality 1.Add the metrics, logs, traces, and alerts that catch issues first, and cut alert noise so real signals stand out. 2.Join the on-call rotation, lead incident debugging, and ship root-cause fixes rather than patches. 3.Improve scalability, reliability, and cloud cost efficiency on AWS. 4.Write design docs, review code, raise test coverage, and mentor junior engineers in your pod. Our Stack You don't need all of this on day one. Strong fundamentals in one language and one database matter more. Area & What we use Languages : Python (primary), TypeScript, Go Frontend : React, TypeScript Backend frameworks : FastAPI, Flask, NestJS AI and LLMs : Amazon Bedrock, AgentCore, Claude, MCP, LangChain / LangGraph Data and search : PostgreSQL (RDS), MongoDB / DocumentDB, DynamoDB, OpenSearch Async and messaging : AWS SQS, SNS, Lambda, Step Functions, EventBridge Cloud and infra : AWS (ECS Fargate, IAM, S3), GCP (Cloud Run), Azure, Docker, Terraform, CloudFormation, Jenkins Integrations : Salesforce APIs (incl. Bulk API, Canvas), HubSpot, AWS ACE, Workato AI development tools : Cursor, Copilot, Claude Code What You Bring 1.5+ years building and running software in production, ideally in a B2B SaaS product. 2.Strong Python or Go, TypeScript with a willingness to work mainly in Python. 3.Hands-on experience with React and TypeScript for production frontends. 4.Solid REST API design and experience with microservices, distributed systems and asynchronous processing, ideally on AWS SQS, SNS and Lambda: queues, retries, idempotency and failure handling. 5.Depth in at least one relational database (PostgreSQL or MySQL) and one NoSQL store (MongoDB or 6.DynamoDB): schema design, indexing and query tuning. 7.Experience building or integrating LLM features, AI agents, RAG or tool-calling systems, with a working grasp of context windows, token management and retrieval. 8.Understanding of TTFT, streaming, latency optimization and caching. 9.Hands-on AWS (and Azure or GCP) production deployments, plus Docker, Git, CI/CD and automated testing. 10.Comfort debugging production issues from logs, metrics and traces. 11.A track record of owning a feature or service from design through production support. 12.Clear written communication: design docs, tickets and updates people can act on. 13.Very important - Proven track record of mentoring and developing junior team members. Nice to Have 1.Hands-on work with MCP servers or clients, Amazon Bedrock or Bedrock AgentCore. 2.Agent orchestration with LangChain or LangGraph, and LLM evaluation, guardrails, or agent observability. 3.Workflow orchestration with Temporal, Airflow, Step Functions, or Celery. 4.CRM integration experience, especially Salesforce or HubSpot APIs. 5.OpenSearch or other vector and search engines for retrieval. 6.Infrastructure as code with Terraform or CloudFormation. 7.Load testing (k6, Locust) and observability tooling. 8.Familiarity with cloud partner programs or marketplaces (AWS ACE, Azure, GCP). How We Work We're a fast-paced startup where a small team ships to large enterprises, and priorities shift with customer needs. You'll thrive here if you: 1.Act like an owner. Your service's uptime, performance, and customer impact are yours, not someone else's ticket. 2.Close the loop. Merged isn't done. You confirm it works in production and follow up until the customer's problem is solved. 3.Move fast without breaking trust. You ship in small, safe increments and know when a shortcut will cost us later. 4.Handle ambiguity. Given a half-formed problem, you ask sharp questions, propose a plan and get moving. 5.Raise problems early. You flag risks, slips and bad ideas, including your own, before they become surprises. 6.Keep learning. You try new AI, agent and cloud tools and bring back what works. 7.Lift the team. You review carefully, share context in writing and help newer engineers level up. What You Get 1.AI in production, not prototypes. Ship agents, RAG, and LLM features that enterprise customers use every day. 2.Hard performance problems. Work on TTFT, streaming, token cost, and high-volume sync at enterprise scale. 3.Real ownership. Own high-impact systems that customer revenue depends on, from design through on-call. 4.Direct customer exposure. Work on enterprise customers' actual problems, not just tickets about them. 5.Room to grow. Shape our platform’s architecture and follow a clear path toward pod lead or tech lead. How to Apply We would love to see what you have built. Send your resume with links to your GitHub or any projects using LLMs or AI agents or any open source contribution.