Forward Deployed Engineer - TS/SCI with Polygraph Required
Role details
Job location
Tech stack
Job description
- Work closely with customers to integrate the LIGER GenAI platform into their existing business processes
- Build and ship features across the full stack: Angular/TypeScript frontend, Node.js/Python backend, PostgreSQL
- Design and implement agentic workflows: tool-calling, multi-step reasoning pipelines, and the orchestration infrastructure that makes them reliable in customer environments
- Build and maintain document processing pipelines supporting text extraction, chunking, metadata enrichment, indexing, and persistence for downstream semantic retrieval use cases
- Ensure successful deployment and initial configuration of the LIGER platform, supporting customers for 60-180 days post-sale before transitioning the deployment to a long-term project team
- Conduct proof-of-concept demonstrations to showcase LIGER's capabilities and its value to potential and existing customers
- Rapidly build features into or around LIGER's core platform to meet customer-specific needs, working closely with the core product team to integrate new features into the product
- Document and communicate customer requirements and feedback to ensure continuous improvement and alignment with customer priorities
- Engage directly with customers in various formats, including in-person, hybrid, or remote work as required by the customer
- Travel occasionally to customer locations within the United States for direct engagements and support
- Work collaboratively with internal teams including product management, engineering, and support to deliver seamless solutions to customers
Requirements
This position requires a TS/SCI with Polygraph
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3+ years of full stack development experience, comfortable owning both frontend and backend
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Proficiency in Angular and TypeScript on the frontend
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Solid backend experience in Node.js and/or Python
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Experience using PostgreSQL to store, retrieve, and manage structured application data, with experience in database design and SQL development
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Hands-on experience building with LLMs (prompt engineering, API integration, tool use, and managing model outputs in production)
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Familiarity with agentic patterns: orchestration, tool-calling, retrieval-augmented generation (RAG), or multi-step agent flows
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Experience designing and developing RESTful APIs and backend services
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Active use of AI-assisted development tools in your day-to-day coding workflow
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Strong knowledge of containerization technologies (e.g. Docker) and CI/CD pipelines, specifically with GitLab
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Familiarity with cloud computing deployment models, especially AWS GovCloud and/or working within a federal environment
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Excellent communication and interpersonal skills, with the ability to interact effectively with multiple stakeholders, including senior executives from government and industry
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Ability to manage multiple tasks in a fast-paced environment and prioritize effectively
What Will Set You Apart
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Background in NLP, computational linguistics, or data science, with hands-on experience in text extraction, entity recognition, embeddings, semantic search, or related techniques
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Experience building scalable document processing pipelines supporting text extraction, chunking, metadata enrichment, indexing, and persistence for downstream semantic retrieval use cases
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Experience with Model Context Protocol (MCP): building servers, defining tools, or integrating MCP into an agent stack
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Familiarity with frameworks like LangChain, LlamaIndex, or similar orchestration tools
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A portfolio of side projects, open-source contributions, or other evidence of a builder's disposition
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Demonstrated fluency with AI coding tools and a workflow that treats them as force multipliers
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Proven ability to work quickly and independently as part of a small team of engineers to deliver high-quality, tailored solutions
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Experience in sales engineering within the federal government sector, with a deep understanding of federal customers' unique challenges and requirements
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Background working on AI-native products or internal tooling where models are core to the user experience, not bolted on
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Familiarity with federal cybersecurity requirements and vulnerability management concepts
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Familiarity with container orchestration engines such as Kubernetes (e.g., EKS, AKS, GKE, OpenShift)
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Strong background in Unix/Linux operating systems
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Knowledge of AWS products and capabilities, with specific experience in GovCloud environments
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Ability to clearly communicate the value and benefits of technical solutions to non-technical audiences