{"id":893364,"url":"https://alion.io/job/neander-founding-engineer","title":"Founding Engineer","company":{"id":714439,"name":"Neander","domain":"neander.ai","url":"https://alion.io/company/neander-2","size_band":"11-50","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"Backend","role_family":"Backend","seniority":null,"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":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Anthropic","optional":false},{"name":"AutoGen","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"CrewAI","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"GCP","optional":false},{"name":"Gemini","optional":false},{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"MySQL","optional":false},{"name":"Node JS","optional":false},{"name":"OpenAI","optional":false},{"name":"PostgreSQL","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Redis","optional":false},{"name":"Rest API","optional":false},{"name":"Semantic Search","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Claude Code","optional":true},{"name":"Copilot","optional":true},{"name":"Cursor","optional":true},{"name":"Fine-tuning","optional":true},{"name":"JavaScript","optional":true},{"name":"Model Context Protocol","optional":true}],"status":"live","first_seen_at":"2026-09-14T08:29:40Z","employer_posted_date":null,"last_verified_at":"2026-09-14T08:29:40Z","board_verified":false,"closed_at":null,"days_open":51,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":51},"description":"We are looking for a Founding Engineer with strong backend and AI expertise to join our early-stage product team. The ideal candidate should be hands-on with backend engineering and have a strong understanding of generative AI, LLMs, AI agents, and agentic AI systems. As a founding engineer, you will work closely with the founding team to design, build, and scale core product features from the ground up. You will have significant ownership and will be involved in technical architecture, product decisions, and engineering execution.\nResponsibilities:\nDesign and develop scalable backend systems, APIs, and microservices.\nBuild AI-powered features using LLMs and generative AI.\nDesign and develop AI agents and agentic AI workflows.\nIntegrate and work with different LLMs such as OpenAI, Anthropic, Gemini, Llama, etc.\nWork with AI tools, frameworks, and APIs to build intelligent applications.\nDevelop RAG (Retrieval-Augmented Generation) pipelines and work with vector databases.\nImplement prompt engineering, tool calling, function calling, structured outputs, and AI workflows.\nBuild systems where AI agents can interact with APIs, databases, tools, and external services.\nEvaluate LLM/agent performance, accuracy, latency, and cost.\nDesign reliable backend architecture for AI applications.\nWork with databases such as PostgreSQL, MySQL, MongoDB, Redis, etc.\nDeploy and scale applications using AWS / GCP / Azure.\nCollaborate closely with product and founding teams to convert ideas into production-ready solutions.\nTake end-to-end ownership of features from ideation, architecture development, and deployment.\nThe core requirements for the job include the following:\nBackend Engineering:\nStrong experience in Python, Java, Go, or Node.js .\nStrong understanding of REST APIs, microservices, distributed systems, and system design.\nExperience with relational and/or NoSQL databases.\nGood understanding of cloud platforms, Docker, Kubernetes, CI/CD, and production systems.\nAI / GenAI:\nStrong understanding of LLMs and generative AI.\nHands-on experience with OpenAI / Anthropic / Gemini / Llama or similar LLM APIs.\nUnderstanding of AI agents and agentic AI architecture.\nExperience with frameworks/tools such as LangChain, LangGraph, LlamaIndex, CrewAI, AutoGen, or similar.\nKnowledge of RAG, embeddings, vector databases, semantic search, and knowledge retrieval.\nUnderstanding of prompt engineering, function/tool calling, context management, and structured outputs.\nFamiliarity with evaluating and monitoring AI applications.\nGood to Have:\nExperience building an AI-first SaaS/product from scratch.\nExperience working in an early-stage startup or founding engineering team.\nKnowledge of MCP (Model Context Protocol) and AI tool integrations.\nExperience with AI coding/development tools such as Cursor, Claude Code, GitHub Copilot, or similar.\nExperience with LLM fine-tuning, model evaluation, or inference optimization.\nStrong product mindset and ability to work with 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