Position: Forward Deployed AI / Software Engineer
Key Responsibilities:
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Work directly with clients to understand business requirements, workflows, technical environments, and operational challenges.
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Translate ambiguous business problems into technical requirements, solution designs, prototypes, and production-ready applications
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Build AI-powered applications, agentic workflows, APIs, data pipelines, and full-stack solutions
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Design and implement systems around AI models, including tools, context, memory, permissions, runtime controls, observability, and feedback mechanisms.
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Build and refine agent workflows covering planning, tool selection, execution, observation, recovery, and termination.
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Develop workflow orchestration using graphs, state machines, and multi-step execution patterns
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Build evaluation mechanisms to measure AI application quality, reliability, task completion, latency, and cost.
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Integrate AI solutions with enterprise applications, APIs, databases, cloud platforms, and third-party services.
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Troubleshoot AI-system issues such as hallucinations, context loss, unreliable tool calls, looping, and prompt-injection risks.
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Collaborate with product, engineering, data, security, and client teams to take solutions from discovery to production.
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Clearly communicate technical decisions, risks, limitations, and trade-offs to technical and non-technical stakeholders.
Required Skills:
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Strong professional experience building and deploying production-grade software.
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Strong proficiency in Python, TypeScript, or a similar programming language.
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Hands-on experience building AI-powered applications or agentic systems.
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Practical understanding of LLMs, prompts, context management, tool use, structured outputs, memory, and model selection.
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Experience building or working with AI aagents/agentloops involving planning, tool use, execution, observation, and recovery.
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Understanding of workflow orchestration, graphs, state machines, or multi-step AI workflows.
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Experience working with APIs, databases, cloud infrastructure, and modern software engineering
practices.
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Experience taking a problem from discovery to prototype to validation to production.
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Ability to work directly with clients or business stakeholders and translate business requirements into technical solutions.
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Strong debugging, problem-solving, communication, and ownership skills.
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Comfortable working remotely with teams operating in CST business hours.
Preferred (Bonus) Skills:
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Experience with AI agent frameworks, workflow engines, coding agents, or custom AI orchestration systems.
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Experience with RAG, embeddings, vector databases/search, knowledge graphs, fine-tuning, or model routing.
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Experience with AI evaluation, regression testing, human evaluation, or production monitoring.
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Familiarity with AI observability, tracing, token/cost analysis, latency monitoring, and quality dashboards.
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Experience building multi-agent or multi-model systems.
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Understanding of AI security risks including prompt injection, data leakage, excessive agency, and
insecure tool usage
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Experience with AWS, Azure, or Google Cloud.
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Experience with Docker, Kubernetes, Infrastructure as Code, and CI/CD.
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Experience in consulting, solutions engineering, professional services, or other customer-facing technical roles.
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Experience working with complex enterprise environments.
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