{"id":3264674,"url":"https://alion.io/job/valuecoders-dt-forward-deployed-ai-software-engineer","title":"[DT] : Forward Deployed AI / Software Engineer","company":{"id":2553864,"name":"ValueCoders","domain":"valuecoders.com","url":"https://alion.io/company/valuecoders-com","size_band":"1-10","is_staffing_agency":false,"employer_type":"staffing","is_intermediary":false,"listed_via":null,"ats_vendor":"Keka","truth_index":{"grade":"B","score":75,"open_postings":9,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":23,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":{"label":"CST","utc_offset_min":-6,"utc_offset_max":-6},"hiring_geo_confidence":"structured","locations":["Noida, 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Outputs","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-10-26T05:36:05Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-31T16:39:16Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Position: Forward Deployed AI / Software Engineer\nKey Responsibilities:\nWork directly with clients to understand business requirements, workflows, technical environments, and operational challenges.\nTranslate ambiguous business problems into technical requirements, solution designs, prototypes, and production-ready applications\nBuild AI-powered applications, agentic workflows, APIs, data pipelines, and full-stack solutions\nDesign and implement systems around AI models, including tools, context, memory, permissions, runtime controls, observability, and feedback mechanisms.\nBuild and refine agent workflows covering planning, tool selection, execution, observation, recovery, and termination.\nDevelop workflow orchestration using graphs, state machines, and multi-step execution patterns\nBuild evaluation mechanisms to measure AI application quality, reliability, task completion, latency, and cost.\nIntegrate AI solutions with enterprise applications, APIs, databases, cloud platforms, and third-party services.\nTroubleshoot AI-system issues such as hallucinations, context loss, unreliable tool calls, looping, and prompt-injection risks.\nCollaborate with product, engineering, data, security, and client teams to take solutions from discovery to production.\nClearly communicate technical decisions, risks, limitations, and trade-offs to technical and non-technical stakeholders.\nRequired Skills:\nStrong professional experience building and deploying production-grade software.\nStrong proficiency in Python, TypeScript, or a similar programming language.\nHands-on experience building AI-powered applications or agentic systems.\nPractical understanding of LLMs, prompts, context management, tool use, structured outputs, memory, and model selection.\nExperience building or working with AI aagents/agentloops involving planning, tool use, execution, observation, and recovery.\nUnderstanding of workflow orchestration, graphs, state machines, or multi-step AI workflows.\nExperience working with APIs, databases, cloud infrastructure, and modern software engineering\npractices.\nExperience taking a problem from discovery to prototype to validation to production.\nAbility to work directly with clients or business stakeholders and translate business requirements into technical solutions.\nStrong debugging, problem-solving, communication, and ownership skills.\nComfortable working remotely with teams operating in CST business hours.\nPreferred (Bonus) Skills:\nExperience with AI agent frameworks, workflow engines, coding agents, or custom AI orchestration systems.\nExperience with RAG, embeddings, vector databases/search, knowledge graphs, fine-tuning, or model routing.\nExperience with AI evaluation, regression testing, human evaluation, or production monitoring.\nFamiliarity with AI observability, tracing, token/cost analysis, latency monitoring, and quality dashboards.\nExperience building multi-agent or multi-model systems.\nUnderstanding of AI security risks including prompt injection, data leakage, excessive agency, and\ninsecure tool usage\nExperience with AWS, Azure, or Google Cloud.\nExperience with Docker, Kubernetes, Infrastructure as Code, and CI/CD.\nExperience in consulting, solutions engineering, professional services, or other customer-facing technical roles.\nExperience working with complex enterprise 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