Forward Deployed Agile Software Engineer

Job Summary

Required Qualifications

• •Professional experience building and deploying production-grade software, ideally including AI-powered or agentic systems.
• •Strong proficiency in Python, TypeScript, or another language commonly used to build AI applications, platforms, and developer tooling.
• •A practical understanding of harness engineering: designing the infrastructure, context, tools, permissions, controls, and feedback mechanisms that enable AI agents to operate reliably.
• •Experience building or working with agent loops, including planning, tool selection, execution, observation, reflection, recovery, and termination.
• •Familiarity with graph-based orchestration, state machines, and multi-step workflows for coordinating agents, tools, data, and human approvals.
• •Experience designing evaluation systems for AI applications, including task-based benchmarks, regression suites, model-graded evaluations, human review, and production monitoring.
• •Understanding of the trade-offs involved in prompts, context management, memory, retrieval, tool use, structured outputs, and model selection.
• •Experience instrumenting AI systems to trace decisions, inspect intermediate states, measure quality, and diagnose failures.
• •Strong knowledge of APIs, distributed systems, databases, cloud infrastructure, and modern software-development practices.
• •Ability to quickly understand unfamiliar systems, technologies, and business domains.
• •Ability to move from an ambiguous customer problem to a working prototype, validate it with real users and evaluations, and evolve it into a secure, maintainable production system.
• •Strong product judgment and the ability to balance model capability, reliability, latency, cost, security, and user experience.
• •Experience collaborating directly with customers, stakeholders, or cross-functional delivery teams.
• •Excellent written and verbal communication skills, including the ability to explain AI-system behavior, limitations, risks, and technical trade-offs clearly.
• •Comfort working in fast-moving environments where requirements and technical constraints continue to evolve.
• •A high degree of ownership, curiosity, empathy, and bias toward action.
• •Ability to travel occasionally for client workshops or on-site delivery, where required.

Desired Qualifications

• •Experience with agent frameworks, workflow engines, coding agents, or custom model-orchestration systems.
• •Experience creating tool interfaces, execution sandboxes, permission models, and human-in-the-loop controls for autonomous or semi-autonomous systems.
• •Familiarity with retrieval-augmented generation, embeddings, vector search, knowledge graphs, fine-tuning, and model-routing strategies.
• •Experience evaluating AI systems using golden datasets, simulators, adversarial testing, online experiments, and production feedback.
• •Familiarity with AI observability, including traces, token and cost analysis, latency measurement, failure classification, and quality dashboards.
• •Experience building systems that use multiple models or specialized agents to complete complex tasks.
• •Understanding of AI security concerns, including prompt injection, data leakage, excessive agency, insecure tool use, and supply-chain risks.
• •Experience with cloud platforms such as AWS, Microsoft Azure, or Google Cloud.
• •Experience with containers, Kubernetes, infrastructure as code, and CI/CD tooling.
• •Contributions to AI infrastructure, evaluation tooling, agent frameworks, or related open-source projects.
• •Experience working in regulated or complex enterprise environments.
• •Experience in consulting, professional services, solutions engineering, sales engineering, or another customer-facing technical role.
• •A history of taking products from initial discovery through production launch and ongoing adoption.