About the role

Position: Forward Deployed AI / Software Engineer

Engagement Mode: Remote

Timezone: United States

Position Overview: We are looking for a Forward Deployed AI / Software Engineer who works at the intersection of software engineering, AI, product development, and client delivery. The role involves working closely with clients to understand business problems, design practical technical solutions, rapidly build prototypes, and take successful solutions into production. The ideal candidate is a hands-on engineer with strong experience building AI-powered applications, agentic workflows, APIs, integrations, and production-grade software systems. This position requires direct client engagement, translating ambiguous business requirements into technical designs, and collaborating across product, engineering, data, security, and client teams throughout the full delivery lifecycle from discovery to production. Candidates must be comfortable working in CST business hours. Key Responsibilities: • Work directly with clients to understand business requirements, workflows, technical environments, and operational challenges • Translate ambiguous business problems into technical requirements, solution designs, prototypes, and production-ready applications • Build AI-powered applications, agentic workflows, APIs, data pipelines, and full-stack solutions • Design and implement systems around AI models, including tools, context, memory, permissions, runtime controls, observability, and feedback mechanisms • Build and refine agent workflows covering planning, tool selection, execution, observation, recovery, and termination • Develop workflow orchestration using graphs, state machines, and multi-step execution patterns • Build evaluation mechanisms to measure AI application quality, reliability, task completion, latency, and cost • Integrate AI solutions with enterprise applications, APIs, databases, cloud platforms, and third-party services • Troubleshoot AI-system issues such as hallucinations, context loss, unreliable tool calls, looping, and prompt-injection risks • Collaborate with product, engineering, data, security, and client teams to take solutions from discovery to production • Clearly communicate technical decisions, risks, limitations, and trade-offs to technical and non-technical stakeholders

Required Skills: • Strong professional experience building and deploying production-grade software • Strong proficiency in Python, TypeScript, or a similar programming language • Hands-on experience building AI-powered applications or agentic systems • Practical understanding of LLMs, prompts, context management, tool use, structured outputs, memory, and model selection • Experience building or working with AI agents / agent loops involving planning, tool use, execution, observation, and recovery • Understanding of workflow orchestration, graphs, state machines, or multi-step AI workflows • Experience working with APIs, databases, cloud infrastructure, and modern software engineering practices • Experience taking a problem from discovery to prototype to validation to production • Ability to work directly with clients or business stakeholders and translate business requirements into technical solutions • Strong debugging, problem-solving, communication, and ownership skills • Comfortable working remotely with teams operating in CST business hours Preferred (Bonus) Skills: • Experience with AI agent frameworks, workflow engines, coding agents, or custom AI orchestration systems • Experience with RAG, embeddings, vector databases/search, knowledge graphs, fine-tuning, or model routing • Experience with AI evaluation, regression testing, human evaluation, or production monitoring • Familiarity with AI observability, tracing, token/cost analysis, latency monitoring, and quality dashboards • Experience building multi-agent or multi-model systems • Understanding of AI security risks including prompt injection, data leakage, excessive agency, and insecure tool usage • Experience with AWS, Azure, or Google Cloud • Experience with Docker, Kubernetes, Infrastructure as Code, and CI/CD • Experience in consulting, solutions engineering, professional services, or other customer-facing technical roles • Experience working with complex enterprise environments