Lead Engineer – AI Powered Platforms

Location: Bangalore (On-site)Experience: 4–8 yearsType: Full-timeAbout AimplifyAt Aimplify, we’re transforming how enterprises operate with intelligent, autonomous AI agents. Our mission is to power next-gen automation using LLMs, multi-agent systems, and real-time data pipelines—across industries like supply chain, finance, compliance, HR, and sustainability.We’re a passionate team of builders, and we’re looking for a Lead Engineer to help us scale our core platforms and define the future of enterprise agentic automation.Role OverviewWe’re hiring a Lead Developer to own critical modules end-to-end, make architecture decisions, and mentor engineers in building AI-powered, agentic applications. You’ll work hands-on across backend, integrations, reliability, and delivery—shipping fast using AI-assisted development and testing practices.What You’ll DoSystem Architecture & Development- Lead the design, architecture, and implementation of enterprise-grade AI agent frameworks for automation. - Build modular, scalable, and secure microservices integrating with LLMs, RAG systems, and enterprise data platforms. - Architect and implement LangGraph / orchestration pipelines for multi-agent collaboration and workflows. - Develop robust APIs (REST/GraphQL) for agent deployment, orchestration, and SaaS consumption. - Lead Playwright/Selenium/Browserbase automation for enterprise-scale browser and workflow automation. - Ensure observability, metering, logging, and monitoring for agent workflows in production.AI & Agent Integration- Integrate and fine-tune LLMs (OpenAI, Claude, Mistral, LLaMA, etc.). - Apply RAG, embeddings (FAISS, Chroma, Pinecone, Milvus, Weaviate), and prompt engineering for enterprise-grade AI use cases.Team Leadership & Collaboration- Mentor and guide engineers in AI/ML, distributed systems, and backend best practices. - Collaborate closely with product, design, and client teams to translate enterprise requirements into scalable solutions. - Drive quality, delivery timelines, and innovation culture across the team.Security & Compliance- Ensure compliance with enterprise security, data governance, and regulatory requirements. - Implement secure coding, RBAC, OAuth2, SSO/SAML, and encryption practices.Technical Skills & Expertise- Programming: Proficiency in Python (FastAPI, LangChain/LangGraph); Node.js/TypeScript preferred. - LLM & AI Ecosystem: Hands-on with OpenAI, Anthropic, LangGraph, LangChain, RAG architectures, and vector databases (Weaviate, Pinecone, Milvus, FAISS). - Data Engineering: Strong experience with multi-source data ingestion, preprocessing, and analytics workflows. - Automation: Experience with Playwright, Selenium, Browserbase for browser automation. - Architecture: Deep knowledge of microservices, distributed systems, and containerization (Docker/Kubernetes). - Cloud & DevOps: Experience with AWS/Azure/GCP, CI/CD pipelines, and IaC (Terraform, Pulumi). - Databases: Proficient in SQL (Postgres, MySQL) + NoSQL (MongoDB, DynamoDB), and vector stores. - Observability & Monitoring: Hands-on with Prometheus, Grafana, ELK, or equivalent. - Security: Skilled in enterprise-grade security practices (OAuth2, SSO/SAML, RBAC, data encryption).What We’re Looking ForMust-Haves- 4–8 years of experience in backend or AI-based system development. - Strong in Java, Python, or Node.js (at least 2). - Experience with LLMs, embeddings, and AI workflows. - Familiarity with multi-agent systems / orchestration frameworks (LangGraph, CrewAI, Autogen). - Hands-on exposure to LLMs in real applications (prompting + tool calling + structured outputs). - Experience integrating AI/ML models into production with reliability concerns (latency, cost, safety). - Production experience with CI/CD and cloud platforms (AWS/GCP/Azure).Nice-to-Haves- Exposure to enterprise domains like finance, HR, supply chain, or compliance. - Prior experience building SaaS or large-scale enterprise platforms. - Strong understanding of observability, metering, and platform reliability. - Experience with agent frameworks: LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, n8n/agentic workflows. - Building RAG pipelines (vector DBs like Pinecone/Weaviate/Milvus, hybrid retrieval, chunking strategies). - LLM evaluation & observability: prompt/versioning, test harnesses, golden datasets, hallucination checks. - Experience with Playwright / browser automation, workflows, and tool-based agents. - Strong testing mindset + automation: contract tests, load tests, e2e frameworks, CI quality gates. - DevEx: creating internal tooling, codegen templates, reusable SDKs, and “paved roads” for faster delivery. - Familiarity with event-driven systems (Kafka/SQS/PubSub), caching (Redis), and performance optimization.Why Join Us- Build the future of enterprise automation with cutting-edge AI. - Be part of a founding team culture with high ownership. - Competitive compensation + ESOPs. - Opportunity to define and scale Aimplify’s core agentic automation platform.

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