Vinove
[DT] : Forward Deployed AI / Software Engineer
Forward-deployed AI/software engineer at Vinove who works directly with clients to turn ambiguous business problems into production AI applications — building agentic LLM workflows, APIs, data pipelines, and full-stack systems. Requires strong Python/TypeScript plus hands-on LLM/agent experience; remote, aligned to CST business hours.
- Compensation
- Not disclosed
- Location
- Remote, UP, India
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- 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
Nice to have
- 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
Full description
Position: Forward Deployed AI / Software EngineerKey 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 aagents/agentloops 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.