OrbitronAI
Forward Deployed Software Engineer
- Compensation
- Not disclosed
- Location
- Bangalore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 8+ years
- Category
- Software engineering
- Posted
Skills
Must have
- 8+ Years of Engineering Experience: Proven track record developing and delivering software architecture, with a heavy focus on AI engineering, intelligent workflows, or advanced product development.
- Agentic Frameworks Mastery: Deep, hands-on experience building complex workflows using LangGraph, LangChain, AutoGen, CrewAI, or custom orchestration loops.
- Advanced Context and Retrieval Engineering: Practical experience implementing knowledge graphs, context Graphs, semantic graph databases (Neo4j, Memgraph, or similar), vector DBs, and advanced RAG top
- State and Memory Design: Understanding of stateful AI application design, including episodic/semantic memory, conversation state management, dynamic context trimming, and long-horizon execution.
- Design and Architecture: Comfortable leading an architecture discussion with a customer's engineering leaders, then doing the work yourself. High agency and a bias for action.
- Forward Deployed Mindset ("Staying Fluid"): Thrives in customer-facing, ambiguous, 0-to-1 environments. High empathy, strong product judgment, and the agility to dynamically adapt technical solutions
- Business Acumen: You don't just question the how but also the whydiscovering impact, architecture design, and deal-winning opportunities.
- Full-Stack and Systems: Comfort operating across Python/TypeScript, modern React interfaces for AI interactions, and cloud API integrations (REST, gRPC, streaming connections).
- Production AI Rigor: Experience with LLM evaluation frameworks (e. g., Ragas, Braintrust, LangSmith), agent tracing, guardrailing, and prompt management.
Full description
Requirements:
- 8+ Years of Engineering Experience: Proven track record developing and delivering software architecture, with a heavy focus on AI engineering, intelligent workflows, or advanced product development.
- Agentic Frameworks Mastery: Deep, hands-on experience building complex workflows using LangGraph, LangChain, AutoGen, CrewAI, or custom orchestration loops.
- Advanced Context and Retrieval Engineering: Practical experience implementing knowledge graphs, context Graphs, semantic graph databases (Neo4j, Memgraph, or similar), vector DBs, and advanced RAG topologies.
- State and Memory Design: Understanding of stateful AI application design, including episodic/semantic memory, conversation state management, dynamic context trimming, and long-horizon execution.
- Design and Architecture: Comfortable leading an architecture discussion with a customer's engineering leaders, then doing the work yourself. High agency and a bias for action.
- Forward Deployed Mindset ("Staying Fluid"): Thrives in customer-facing, ambiguous, 0-to-1 environments. High empathy, strong product judgment, and the agility to dynamically adapt technical solutions on the fly without getting bogged down by rigid specs.
- Business Acumen: You don't just question the how but also the whydiscovering impact, architecture design, and deal-winning opportunities.
- Full-Stack and Systems: Comfort operating across Python/TypeScript, modern React interfaces for AI interactions, and cloud API integrations (REST, gRPC, streaming connections).
- Production AI Rigor: Experience with LLM evaluation frameworks (e. g., Ragas, Braintrust, LangSmith), agent tracing, guardrailing, and prompt management.