Forward Deployed Engineer

Candidates typically face a three‑stage process: an online coding test focusing on DS&A, a technical interview that probes system design, AI/ML fundamentals, and past project experience, followed by an HR round assessing cultural fit and motivation. The difficulty is moderate, and preparation on real‑world problem solving and clear communication helps greatly.

Round 1: Online coding assessment (Data structures & algorithms) → Round 2: Technical interview (system design, AI/ML concepts, past projects) → Round 3: HR interview (fit, motivation, cultural alignment)

DehazeLabs is an emerging AI‑focused services partner of Anthropic, dedicated to turning cutting‑edge large language models into practical, enterprise‑grade agents. The company works with a diverse set of businesses – from fintech to logistics – helping them automate complex workflows, improve decision‑making speed, and unlock new revenue streams through intelligent automation. With a small but highly skilled engineering team, DehazeLabs emphasizes rapid prototyping, close customer collaboration, and a relentless focus on measurable business impact. The culture is fast‑paced, merit‑based, and encourages engineers to wear multiple hats – from product discovery to production operations.

Bachelor's degree (B.Tech/B.E./B.Sc./MCA) in Computer Science, Information Technology, Electronics, or related fields. Strong problem‑solving aptitude and willingness to work directly with enterprise customers.

DehazeLabs is an emerging AI‑focused services partner of Anthropic, dedicated to turning cutting‑edge large language models into practical, enterprise‑grade agents. The company works with a diverse set of businesses – from fintech to logistics – helping them automate complex workflows, improve decision‑making speed, and unlock new revenue streams through intelligent automation. With a small but highly skilled engineering team, DehazeLabs emphasizes rapid prototyping, close customer collaboration, and a relentless focus on measurable business impact. The culture is fast‑paced, merit‑based, and encourages engineers to wear multiple hats – from product discovery to production operations. As a Forward Deployed Engineer (FDE), you will sit at the intersection of engineering, product, and customer success. You will embed directly with client teams, spend time understanding their day‑to‑day processes, and translate vague operational challenges into concrete technical solutions. The role is ideal for fresh graduates who love to dive into real‑world problems, enjoy building end‑to‑end systems, and are excited about the practical applications of generative AI. You will own the entire lifecycle of an AI‑agent deployment – from discovery workshops, through prototype building, to production rollout, monitoring, and iterative improvement based on real‑world metrics. Key responsibilities include: 1. Conduct on‑site or virtual discovery sessions with enterprise customers to map existing workflows and identify automation opportunities. 2. Draft clear technical specifications and roadmaps that turn loosely defined problems into actionable engineering plans. 3. Design, develop, and integrate AI agents using Python, LangChain, FastAPI, and cloud services (AWS/GCP). 4. Build robust API integrations, data pipelines, and micro‑service architectures that connect the agents to customer tools such as CRM, ERP, and data warehouses. 5. Deploy solutions on Docker/Kubernetes clusters, ensuring scalability, reliability, and security. 6. Set up observability, logging, and alerting to monitor agent performance and business KPIs. 7. Conduct A/B testing with real‑world data, measure impact on efficiency or cost, and iterate on the solution. 8. Document reusable patterns, libraries, and best‑practice guides for future deployments. 9. Collaborate closely with DehazeLabs product and core engineering teams to feed back customer insights and influence platform roadmap. 10. Provide post‑deployment support, troubleshooting, and knowledge transfer to client technical teams. Tech Stack: Python, LangChain, FastAPI, Docker, Kubernetes, AWS/GCP, REST/GraphQL APIs, PostgreSQL/NoSQL, CI/CD pipelines, LLMs (Claude, GPT‑4), Git. Growth Path: Starting as a Junior Forward Deployed Engineer, you can progress to Senior FDE, then to Solutions Architect or Product Lead, eventually moving into leadership roles such as Head of Enterprise Solutions. The role offers exposure to both deep technical work and high‑impact business engagements, making it a fast track for ambitious engineers. Why Join DehazeLabs? You will work on the frontier of applied AI, solving tangible problems for Fortune‑500 clients while gaining hands‑on experience with the latest LLM technologies. The remote‑first policy gives you flexibility, and the small team environment ensures your contributions are visible and directly shape the company’s direction. If you are curious, customer‑obsessed, and eager to see your code drive real business outcomes, DehazeLabs provides the perfect launchpad.