{"id":2508980,"url":"https://alion.io/job/labra-senior-software-engineer","title":"Senior Software Engineer","company":{"id":2869096,"name":"Labra","domain":"labra.io","url":"https://alion.io/company/labra-io","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Wellfound","truth_index":null},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":2500000,"max":3200000,"currency":"INR","period":"year","gross":true,"usd_annual":33750},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon EventBridge","optional":false},{"name":"Amazon S3","optional":false},{"name":"AWS","optional":false},{"name":"AWS Lambda","optional":false},{"name":"AWS Step Functions","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CloudFormation","optional":false},{"name":"Docker","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Git","optional":false},{"name":"Go","optional":false},{"name":"Google Cloud Run","optional":false},{"name":"IAM","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"React.js","optional":false},{"name":"Rest API","optional":false},{"name":"Terraform","optional":false},{"name":"Tool Use","optional":false},{"name":"TypeScript","optional":false},{"name":"WebSockets","optional":false},{"name":"Amazon DocumentDB","optional":true},{"name":"Amazon ECS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"AWS Bedrock AgentCore","optional":true},{"name":"AWS Fargate","optional":true},{"name":"Claude","optional":true},{"name":"DynamoDB","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"JavaScript","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"Nest.JS","optional":true},{"name":"Node JS","optional":true},{"name":"OpenSearch","optional":true},{"name":"PostgreSQL","optional":true}],"status":"live","first_seen_at":"2026-10-14T04:28:05Z","employer_posted_date":null,"last_verified_at":"2026-10-14T04:28:05Z","board_verified":false,"closed_at":null,"days_open":3,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":3},"description":"Role : Senior Software Engineer\n\nCloud & AI - Labra - Bengaluru (In-office)\n\nBuild the AI agents, sync engine, and full-stack product that keep enterprise CRMs and cloud partner programs in lockstep, and own them in production.\n\nAbout Labra : \n\nLabra 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.\n\nThe Role : \n\nThis 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.\n\nYou'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.\n\nWhat You'll Own : \n\nAI agents and LLM features : \n\n- Build production AI agents and LLM features with RAG, tool calling, and MCP-based workflows.\n\n- Design context management : memory, compression, retrieval and prompt optimization.\n\n- Optimize for time to first token (TTFT), latency, token usage, and cost through caching, parallel tool execution, and reducing unnecessary LLM calls.\n\n- Ship streaming AI experiences over SSE and WebSockets.\n\nSync engine and integrations : \n\n- Design, build and ship modules for various business systems (such as CRM, ERPs) integrations, sync configuration and co-sell pipeline visibility.\n\n- Make high-volume, bidirectional sync between CRMs and cloud partner programs fast, correct and recoverable.\n\n- Build event-driven processing on AWS SQS, EventBridge, SNS, Lambda, and Step Functions, with robust retries, idempotency, and dead-letter handling.\n\nFull-stack product : \n\n- Build customer-facing features in React and TypeScript, backed by well-designed REST APIs and services in Python or Go.\n\n- Implement authentication, authorization, RBAC, and secure third-party integrations.\n\n- Profile slow endpoints and queries, tune connection pools and aggregation pipelines, and load-test before customers hit the limits.\n\n- Write automation and unit tests for the code before it is deployed.\n\nProduction and engineering quality : \n\n- Add the metrics, logs, traces, and alerts that catch issues first, and cut alert noise so real signals stand out.\n\n- Join the on-call rotation, lead incident debugging, and ship root-cause fixes rather than patches.\n\n- Improve scalability, reliability, and cloud cost efficiency on AWS.\n\n- Write design docs, review code, raise test coverage, and mentor junior engineers in your pod.\n\nTech Stack : \n\n- Languages : Python (primary), TypeScript, Go\n\n- Frontend : React, TypeScript\n\n- Backend frameworks : FastAPI, Flask, NestJS\n\n- AI and LLMs : Amazon Bedrock, AgentCore, Claude, MCP, LangChain / LangGraph\n\n- Data and search : PostgreSQL (RDS), MongoDB / DocumentDB, DynamoDB, OpenSearch\n\n- Async and messaging : AWS SQS, SNS, Lambda, Step Functions, EventBridge\n\n- Cloud and infra : AWS (ECS Fargate, IAM, S3), GCP (Cloud Run), Azure, Docker, Terraform, CloudFormation, Jenkins\n\nWhat You Bring : \n\n- 5+ years building and running software in production, ideally in a B2B SaaS product.\n\n- Strong Python or Go, TypeScript with a willingness to work mainly in Python.\n\n- Hands-on experience with React and TypeScript for production frontends.\n\n- Solid REST API design and experience with microservices, distributed systems and asynchronous processing.\n\n- Depth in at least one relational database and one NoSQL store.\n\n- Experience building or integrating LLM features, AI agents, RAG or tool-calling systems.\n\n- Hands-on AWS production deployments, plus Docker, Git, CI/CD and automated testing.\n\n- A track record of owning a feature or service from design through production support.\n\n- Proven track record of mentoring and developing junior team members.\n\nSkills\nAgentic AI, LLM, Artificial Intelligence, RAG, AWS, TypeScript, Full Stack, Python, Golang, React.js","description_format":"text","description_chars":4254,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Cybersecurity","Penetration Testing","Identity 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