Software Engineer 3 – GenAI

Bidgely

. Design and build production multi-agent systems including supervisor/router and specialist agents, LangGraph workflows, tool calling, conversation memory, and checkpointing .

Posted 11/12/2026full-timeRemote • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building multi-agent systems, with strong capabilities in Python and Java, and hands-on experience with LLM APIs and agent orchestration frameworks. Proven ability to manage system performance, implement security measures, and mentor engineering teams while effectively communicating technical designs and progress.

Highest-signal resume keywords

Python ProgrammingLLM API ExperienceLangChain FrameworkBackend API DesignAWS Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Software EngineeringAgent OrchestrationRAG Systems DevelopmentTool/Function CallingData ManagementSystem DesignAnalytical SkillsDebuggingLatency ManagementScalable Services

Soft Skills

Communication SkillsMentoringCollaboration

Tools & Technologies

LangGraphOpenAIAmazon BedrockPostgreSQLRedisEKSLangSmithCI/CD

Industry Keywords

Multi-Tenant SaaSEnergy and UtilitiesIoTSmart Meter DataData Privacy

Tech Stack

Tools & technologies

AWSIoTJavaPostgresPythonRedis

About the role

Key responsibilities & impact

Design and build production multi-agent systems including supervisor/router and specialist agents, LangGraph workflows, tool calling, conversation memory, and checkpointing
Build typed tool contracts and data-access layers over Bidgely APIs so the LLM explains results instead of generating numbers
Develop RAG pipelines for utility tariff and knowledge retrieval with tenant-isolated embeddings and retrieval
Manage latency, reliability, and cost through caching, prewarming, retries, circuit breakers, and model routing
Implement guardrails for prompt injection, scope control, authorization, tenant isolation, and data management
Build observability and evaluation hooks with LangSmith and collaborate with SDETs on evaluation datasets, regression suites, and release criteria
Debug agent failures in production using traces, logs, and metrics, and drive root-cause fixes
Support streaming through WebSocket/SSE and widget integration with front-end teams
Lead design and code reviews, set engineering standards, and mentor SDE1 and SDE2 engineers
Communicate designs, trade-offs, and progress to engineering, product, and leadership

Requirements

What you’ll need

6–10 years of software engineering experience, including at least 1–2 years building and shipping LLM or GenAI features in production
Strong Python skills and good working knowledge of Java
Hands-on experience with LangChain, LangGraph, or similar agent orchestration frameworks
Experience with LLM APIs (OpenAI, Anthropic, Amazon Bedrock), prompt design, tool/function calling, and structured outputs
Experience building RAG systems with embeddings and vector stores (e.g., pgvector)
Strong backend and API design skills, with experience building scalable, low-latency services
Experience with AWS, containers (EKS), PostgreSQL, Redis, and CI/CD
Experience with evals, LLM-as-judge, or AI observability tools such as LangSmith
Strong system design, analytical, and communication skills
Experience with time-series, IoT, smart meter data, energy and utilities, voice or IVR GenAI products, multi-tenant SaaS, security, or data privacy is nice to have

Benefits

Comp & perks

Remote work arrangement
Great Place to Work-certified Bengaluru engineering center