Forward Deployed Engineer

Key Responsibilities

• Work directly with customers and internal stakeholders to understand business challenges, technical requirements, and desired outcomes.
• Design, develop, and deploy AI-powered applications using LLMs, Python, and modern AI technologies.
• Build prototypes and proof-of-concepts rapidly, iterate based on feedback, and transition successful solutions into production.
• Integrate LLMs with APIs, databases, enterprise applications, and existing technology stacks.
• Develop reliable Python services, automation workflows, data pipelines, and backend components.
• Evaluate LLM outputs, improve prompts and workflows, and contribute to the development of robust AI systems.
• Collaborate closely with product managers, software engineers, data scientists, and customer teams to deliver end-to-end solutions.
• Troubleshoot technical issues in production environments and identify opportunities for improving system performance, reliability, and scalability.
• Translate ambiguous customer requirements into practical technical solutions.
• Communicate technical concepts clearly to both technical and non-technical stakeholders.
• Stay current with developments in GenAI, LLM architectures, AI agents, model APIs, and emerging AI engineering practices.

Must-Have Skills

• AI / Artificial Intelligence
• Large Language Models (LLMs)
• Strong programming experience in Python
• Experience building or integrating AI/ML-powered applications.
• Understanding of LLM APIs, prompt engineering, model evaluation, and AI application development.
• Strong problem-solving and debugging abilities.
• Experience working directly with customers, users, or cross-functional stakeholders.
• Ability to operate effectively in ambiguous and fast-changing environments.
• Strong communication and collaboration skills.

Good-to-Have Skills

• Experience with C# / .NET or other backend programming languages.
• Hands-on experience with Generative AI (GenAI) applications.
• Exposure to AI agents, RAG pipelines, vector databases, embeddings, and tool calling.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with APIs, microservices, databases, and distributed systems.
• Experience deploying AI applications into production environments.
• Strong stakeholder management and customer-facing experience.