Job Description
Location: Bangalore (On-site)
Experience: 4–8 years
Type: Full-time
About Aimplify
At 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 Overview
We’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 Do
System 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 Lang Graph / orchestration pipelines for multi-agent collaboration and workflows.
- Develop robust APIs (REST/Graph QL) for agent deployment, orchestration, and Saa S 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 (Open AI, Claude, Mistral, LLa MA, 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 (Fast API, Lang Chain/Lang Graph); Node.js/Type Script preferred.
- LLM & AI Ecosystem: Hands-on with Open AI, Anthropic, Lang Graph, Lang Chain, 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 & Dev Ops: Experience with AWS/Azure/GCP, CI/CD pipelines, and Ia C (Terraform, Pulumi).
- Databases: Proficient in SQL (Postgres, My SQL) + No SQL (Mongo DB, Dynamo DB), 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 For
Must-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 (Lang Graph, Crew AI, 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 Saa S or large-scale enterprise platforms.
- Strong understanding of observability, metering, and platform reliability.
- Experience with agent frameworks: Lang Graph, Lang Chain, Semantic Kernel, Auto Gen, Crew AI, 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.
- Dev Ex: creating internal tooling, codegen templates, reusable SDKs, and “paved roads” for faster delivery.
- Familiarity with event-driven systems (Kafka/SQS/Pub Sub), 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.
Experience: 4–8 years
Type: Full-time
About Aimplify
At 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 Overview
We’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 Do
System 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 Lang Graph / orchestration pipelines for multi-agent collaboration and workflows.
- Develop robust APIs (REST/Graph QL) for agent deployment, orchestration, and Saa S 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 (Open AI, Claude, Mistral, LLa MA, 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 (Fast API, Lang Chain/Lang Graph); Node.js/Type Script preferred.
- LLM & AI Ecosystem: Hands-on with Open AI, Anthropic, Lang Graph, Lang Chain, 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 & Dev Ops: Experience with AWS/Azure/GCP, CI/CD pipelines, and Ia C (Terraform, Pulumi).
- Databases: Proficient in SQL (Postgres, My SQL) + No SQL (Mongo DB, Dynamo DB), 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 For
Must-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 (Lang Graph, Crew AI, 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 Saa S or large-scale enterprise platforms.
- Strong understanding of observability, metering, and platform reliability.
- Experience with agent frameworks: Lang Graph, Lang Chain, Semantic Kernel, Auto Gen, Crew AI, 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.
- Dev Ex: creating internal tooling, codegen templates, reusable SDKs, and “paved roads” for faster delivery.
- Familiarity with event-driven systems (Kafka/SQS/Pub Sub), 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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