Forward Deployed Engineer
Role details
Job location
Tech stack
Job description
We are seeking a highly autonomous and client-facing Forward Deployed Engineer to sit directly at the intersection of Product Engineering and Enterprise Solutions. This role requires an exceptional software engineering foundation combined with deep cloud proficiency, generative AI fluency, and the strategic communication skills necessary to solve complex enterprise problems live.
Core Responsibilities
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Enterprise Architecture: Partner closely with customer technical leadership to translate abstract business goals into highly resilient, production-ready AI pipelines.
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AI Application Development: Design, build, and optimize robust REST APIs, microservices, and workflows leveraging standard LLMs, vector search, and complex chunking mechanisms.
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Rapid Prototyping: Develop compelling, high-performance Proof of Concepts (PoCs) and seamlessly transition them into long-term enterprise production features.
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Cross-Functional Velocity: Serve as the primary technical feedback loop between the client deployment and internal Product and Core Engineering teams to drive the platform's core roadmap.
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System Optimization: Troubleshoot distributed system performance bottlenecks, optimize vector query latencies, and guarantee robust infrastructure scale.
Requirements
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Experience: 5-8 years of professional software engineering experience shipping production-grade applications.
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Core Languages: Advanced proficiency in Python (highly preferred), Java, or TypeScript.
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Generative AI & LLMs: Proven experience building real-world software workflows with OpenAI, Azure OpenAI, Anthropic, or open-source LLMs alongside frameworks like LangChain or LlamaIndex.
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Data Architecture: Hands-on depth with RAG (Retrieval-Augmented Generation) architectures, vector databases (e.g., Pinecone, Milvus, Qdrant, or pgvector), and relational/non-relational systems (SQL/NoSQL).
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Cloud & DevOps: Strong mastery of AWS, Azure, or Google Cloud Platform cloud platforms paired with Docker, Kubernetes, Git, and advanced modern CI/CD patterns.
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Client Presence: Demonstrated background in technical customer-facing environments, with the ability to confidently influence and navigate enterprise technical stakeholders.
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Previous experience inside an elite, fast-paced product-based SaaS or venture-backed AI startup.
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Deep understanding of semantic chunking, embedding finetuning, and evaluation metrics for large language models.