Forward Deployed Engineer/AI Solutions Engineer

This role combines software engineering, solution architecture, consulting, product thinking, and customer-facing execution. The ideal candidate should be comfortable moving between customer conversations, messy business workflows, technical design, rapid prototyping, integration, deployment, and product feedback.

Key Responsibilities:

• Work closely with customers to understand business processes, pain points, operational bottlenecks, system landscape, data flows, and success metrics.
• Translate customer problems into technical solution designs, prototypes, MVPs, integrations, automations, or product configurations.
• Build hands-on solutions using modern engineering practices across APIs, databases, cloud platforms, workflow tools, enterprise systems, and AI/GenAI technologies.
• Develop proof-of-concepts and pilots that can demonstrate business value quickly and evolve into production-grade implementations.
• Integrate solutions with enterprise applications such as ERP, CRM, data platforms, workflow systems, collaboration tools, and third-party APIs.
• Partner with product, engineering, design, delivery, and customer success teams to convert repeated customer needs into reusable platform capabilities.
• Support customer deployments, testing, troubleshooting, user adoption, and handover to delivery or support teams.
• Create technical documentation, architecture notes, implementation playbooks, demo scripts, reusable components, and customer-specific solution guides.
• Act as the technical bridge between the customer and internal product/engineering teams.
• Identify opportunities for automation, AI adoption, data improvement, process redesign, and platform expansion.
• Bring back field learnings to influence product roadmap, engineering priorities, reusable accelerators, and go-to-market propositions.

Required Skills and Experience:

• 3–8 years of experience in software engineering, solution engineering, implementation engineering, product engineering, technical consulting, or customer-facing technology roles.
• Strong software engineering fundamentals and hands-on experience in at least one major programming language such as Python, JavaScript/TypeScript, Java, C#, or Go.
• Good understanding of APIs, databases, cloud services, authentication, system integration, and application deployment.
• Ability to understand business workflows and convert them into clear technical designs.
• Experience building prototypes, MVPs, internal tools, dashboards, automations, or production grade applications.
• Comfortable working with structured and unstructured data.
• Strong problem-solving skills with the ability to navigate ambiguity and incomplete information.
• Ability to communicate clearly with both technical and non-technical stakeholders.
• Comfortable working in fast-moving customer environments where requirements evolve quickly.
• Strong ownership mindset and ability to take a problem from discovery to working solution.

Good to Have:

• Experience with GenAI, LLMs, RAG, agents, AI workflow automation, prompt engineering, or model integration.
• Experience integrating with enterprise systems such as Salesforce, SAP, Oracle, ServiceNow, Workday, Microsoft Dynamics, HubSpot, Jira, or similar platforms.
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with data engineering, ETL/ELT pipelines, BI dashboards, analytics platforms, and reporting workflows.
• Experience in consulting, pre-sales engineering, solution architecture, implementation, or product-led delivery.
• Exposure to industries such as retail, BFSI, healthcare, manufacturing, telecom, media, travel, or technology services.
• Experience working with customers during pilots, demos, workshops, discovery sessions, and production rollouts..

Sample Projects This Role May Work On:

• Build a GenAI assistant that helps customer service teams search enterprise knowledge and resolve cases faster.
• Create an automation that connects CRM, ERP, and reporting systems to reduce manual work.
• Develop a prototype that uses customer data to generate insights, recommendations, or next best actions.
• Integrate an AI workflow into an existing business process such as order management, finance operations, HR support, marketing operations, or procurement.
• Build dashboards, internal tools, and lightweight applications to help customers make faster decisions.
• Turn a repeated customer implementation pattern into a reusable product feature or accelerator.