Forward Deployed Agile Software Engineer
New
J
JobgetherAI software
Workplace type: Remote; based in IndiaFull-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonTypeScriptRESTful APIsDistributed Systems
Requirements
- Demonstrated experience building and deploying production-grade software, ideally including AI-powered applications, autonomous agents, or agentic systems.
- Strong skills in Python, TypeScript, or another programming language commonly used for AI applications, platforms, and developer tooling.
- Practical understanding of designing AI agent infrastructure, including context, tools, permissions, controls, and feedback mechanisms.
- Experience building or working with agent loops involving planning, tool selection, execution, observation, reflection, recovery, and termination.
- Familiarity with graph-based orchestration, state machines, and multi-step workflows coordinating agents, tools, data, and human approvals.
- Experience designing AI application evaluations, including task-based benchmarks, regression suites, model-graded evaluations, human review, and production monitoring.
- Knowledge of prompt design, 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 understanding of APIs, distributed systems, databases, cloud infrastructure, and modern software development practices.
- Experience collaborating directly with customers, stakeholders, or cross-functional delivery teams.
- Ability to explain AI behavior, limitations, risks, and technical trade-offs clearly.
- Willingness to travel occasionally for client workshops or on-site delivery when required.
Responsibilities
- Partner with clients and internal teams to understand business objectives, workflows, technical environments, data sources, and constraints.
- Translate ambiguous challenges into requirements, solution architectures, prototypes, and delivery plans.
- Design, develop, and deploy AI-enabled applications, agentic workflows, APIs, developer tools, data pipelines, and full-stack products.
- Build AI harness infrastructure for prompts, tools, context, memory, permissions, runtime controls, observability, and feedback.
- Develop agent loops and workflows using planning, tool selection, execution, observation, reflection, recovery, and termination patterns.
- Create evaluation frameworks and testing strategies to measure task completion, accuracy, reliability, safety, latency, cost, and user value.
- Turn validated prototypes into secure, scalable, maintainable production systems and integrate them with client systems and enterprise data.
- Establish safeguards, permission boundaries, approval mechanisms, and fallback strategies for AI systems.
- Instrument applications, troubleshoot technical and operational issues, and use production insights to improve reliability.
- Collaborate with product, design, engineering, data, security, and client stakeholders; share reusable patterns and implementation insights.
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