Job Description
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.
