Job Title:  Senior Consultant | API Developer | Pan India | Engineering | Platform Development & Integration

The team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.       

Your work profile

We are seeking a hands-on Forward Deployed Engineer who can work directly with users, rapidly prototype GenAI solutions, and convert validated concepts into secure, production-ready applications. The candidate should combine GenAI engineering expertise with strong API, integration, automation and end-to-end software delivery capabilities.

The Forward Deployed Engineer works close to business users, product teams and delivery squads as the accountable engineer for rapid prototyping and end-to-end solution delivery. The role converts real user needs into secure, production-viable software across user interfaces, APIs, integrations and automation. It bridges product intent and engineering execution, accelerating time-to-value while ensuring solutions are scalable, supportable and aligned with enterprise standards.

• User-adjacent discovery and rapid prototyping: Work directly with users to understand workflows and pain points; translate needs into prototypes, demonstrations and thin-slice implementations that validate value quickly.
• End-to-end solution engineering: Design and implement complete solutions spanning modern user interfaces, APIs/services, integrations, events and automation using approved platforms and patterns.
• Solution shaping and technical options: Define pragmatic technical approaches, MVP scope and delivery sequencing; balance speed with security, resilience, maintainability and cost.
• Integration and automation enablement: Build system, API and event integrations; automate workflows, controls and reporting to remove manual steps and improve reliability.
• Engineering quality and controls: Apply secure coding, automated testing, code quality, CI/CD and enterprise control requirements; identify risks and control gaps early.
• Production readiness and handover: Establish logging, monitoring, runbooks, support ownership and non-functional readiness so solutions can operate safely at scale.
• Reuse and platform alignment: Prefer reusable services and established patterns over bespoke builds; contribute components, templates and reference implementations to engineering communities.
• Stakeholder and dependency management: Communicate progress, options, trade-offs, dependencies and risks clearly; keep decisions unblocked and delivery moving.

Key skills

• Proven delivery of end-to-end software solutions covering UI, APIs/services and upstream/downstream system integration.
• Rapid prototyping with users, iterative validation and subsequent hardening toward production readiness.
• Build and deploy GenAI and agentic applications: RAG, tool-using agents, multi-agent orchestration and workflow automation.
• Design evaluation, guardrails, cost controls and human-in-the-loop checks suited to regulated environments.
• Enterprise integration and automation using workflows, orchestration, scripting and CI/CD automation.
• Working knowledge of secure engineering, automated testing, observability including logs, metrics and traces, and operational handover.
• Experience partnering with product and business stakeholders to shape MVP scope, priorities and trade-offs.
• Ability to deliver in ambiguous environments with shifting requirements while maintaining transparency and engineering discipline.
• Practical use of vector databases and GenAI or agent frameworks such as LangGraph, Semantic Kernel or equivalent. The specific technology stack is not intended to be restrictive.
• REST APIs, enterprise-system integration, containerisation and Git-based CI/CD delivery.
• Experience with modern front-end frameworks such as React or Angular, or equivalent UI technologies.
• Hands-on development using Python or an equivalent backend language, with production-grade API implementation.
• Delivery within regulated or controlled environments, including risk, audit, security and data-handling requirements.
• Platform-based delivery using shared services, APIs, integration platforms and enterprise tooling, with sound reuse-versus-build judgment.
• Modern UI frameworks, API design, event-driven architecture, integration patterns and automation/orchestration tooling.
• Product-led, transformation-pod or embedded engineering delivery models.
• Creation of reusable accelerators such as templates, reference applications and integration patterns, plus coaching of other engineers.
• Experience with multi-agent orchestration, Model Context Protocol (MCP), vector databases and LLM evaluation tooling.