Senior Forward-Deployed Engineer / Incubation Lead

Role Overview

This opportunity is for a senior hands-on engineer who can sit with business stakeholders, turn unclear product concepts into usable prototypes, and help a small pod move quickly through build, demo, and feedback loops. The role calls for strong full-stack development depth, practical AI/GenAI capability, and the ability to convert product direction into working solutions. For lead-focused candidates, the position also includes mentoring, architecture ownership, and direct stakeholder-facing responsibility.

Key Responsibilities

• Work closely with business subject-matter experts and product stakeholders to understand business challenges and spot opportunities for prototyping.
• Build fast prototypes across the frontend, backend, APIs, data connections, cloud setup, and AI workflows.
• Convert strategy and loosely defined needs into technical designs and functioning demos.
• Run frequent build-demo-feedback cycles with an execution-first approach and visible progress.
• Coach a pod of 4 to 5 engineers and help them work with strong independence.
• Advise on architecture, API structure, data models, cloud deployment, AI integration, and security considerations.
• Assess feasibility, identify risks, weigh trade-offs, and suggest practical implementation choices.
• Create prototypes that can be reviewed for pilot funding and, if approved, transition into delivery work.
• Assist with hiring by taking part in technical screening, whiteboarding, and prototype-based evaluations.

Technical Stack and Experience Areas

Frontend: React.js, TypeScript, Next.js, JavaScript, single-page application design, responsive UI, API integration, Redux, React Query, Tailwind CSS, Material UI, Ant Design.

Backend: Python, FastAPI, REST APIs, Node.js, GraphQL, authentication, authorization, Celery, asynchronous processing, serverless APIs.

AI / GenAI: Generative AI, large language models, prompt engineering, retrieval-augmented generation, embeddings, vector search, agentic AI, LangChain, LlamaIndex, OpenAI API, Azure OpenAI, AI guardrails, AI observability.

Cloud & AWS: AWS, Lambda, API Gateway, S3, RDS, Aurora, IAM, CloudWatch, ECS, Fargate, EKS, Kubernetes, EventBridge, SQS, SNS, DynamoDB, VPC, Terraform, AWS CDK.

Databases: PostgreSQL, SQL, MongoDB, Redis, DynamoDB, OpenSearch, Pinecone, pgvector, data modeling, data integration.

DevOps: Docker, Git, CI/CD, GitHub Actions, GitLab CI, automated testing, logging, monitoring, secure SDLC.

Architecture & Design: system design, microservices, API design, scalable architecture, event-driven architecture, security architecture, platform integration.

Enterprise & Productivity Tools: Palantir Foundry, Replit, AI coding assistants, workflow automation.

Leadership & Product: technical leadership, stakeholder management, product engineering, rapid prototyping, greenfield development, solution architecture, team mentoring, incubation leadership.

Must-Have Capabilities

• Strong practical ability across frontend, backend, data, cloud, and deployment layers.
• Hands-on experience building or integrating AI and GenAI capabilities.
• Comfort with rapid prototyping and iterating quickly from business feedback.
• Sound architecture judgment that balances speed with future scalability.
• Ability to engage directly with business SMEs, ask precise questions, and manage expectations well.
• For lead-level profiles, the ability to mentor engineers, review designs, and keep execution moving.
• Comfort starting from a blank slate and taking a concept to a working solution.

Experience Expectations

• The target experience range is 8 to 16 years for lead or architect-track profiles.
• Product engineering experience is required.
• Backgrounds from startups, greenfield builds, or innovation labs are strongly preferred.

Preferred Candidate Profile

• Experience in product engineering or full-stack software development.
• History of building greenfield products, MVPs, internal platforms, prototypes, or customer-facing product features.
• Exposure to AI assistants, automation workflows, RAG, agentic AI, or LLM-based applications.
• Prior work in startup, product engineering, innovation, or incubation settings.
• Comfort using tools such as Palantir, Replit, AI coding assistants, and rapid-build platforms.
• Previous experience as an architect, tech lead, incubation lead, or pod lead is an advantage for senior candidates.
• Preference for candidates based in Hyderabad or willing to work from Hyderabad.

Working Model

• The team works directly with business SMEs rather than following a traditional requirement-heavy delivery approach.
• The day-to-day flow is iterative: define the need, build a prototype, demo it, collect feedback, and refine.
• Pods generally consist of 4 to 5 engineers and are expected to operate with about 70% self-sufficiency, supported by roughly 30% guidance from the incubation lead.
• Prototype work is not immediately treated as production delivery; successful pilots are reviewed for funding before moving into a delivery track.
• Soft skills carry as much weight as technical strengths, including critical thinking, communication, stakeholder engagement, and handling ambiguity.

Eligibility

Any graduate can apply. The role is best suited to candidates with strong product engineering and full-stack experience, especially those comfortable working in Hyderabad or relocating there.

Company Overview

Tanisha Systems, established in 2002 in Massachusetts, USA, provides custom application development and end-to-end IT services to clients around the world. The company follows a client-focused engagement model that blends local on-site and off-site support with the advantages of offshore delivery, including cost efficiency, global expertise, and quality. Its services include custom application development, application modernization, business process outsourcing, and professional IT services delivered from offices in the USA and India.

Additional Information

This is a full-time role based in Hyderabad, India. The position is centered on incubation, rapid prototyping, and stakeholder-driven product development.