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About Client Our Client is founded by IIT Kanpur graduates (2005 batch) operates 3 verticals: - AI & ML services - building artificial-intelligence solutions for clients in the US. - Media Analytics - working with large You Tube channels and media houses. - Talent Solutions - meeting staffing and technology-hiring needs for large enterprises and mid-size companies. The selected person is hired as a full time employee (FTE) on our client's payroll and is deployed to work on the end client's projects. About the Engagement The engagement sits inside the engineering organisation of a large global financial services enterprise. The team is standing up agentic AI and AI-assisted software development capability across multiple engineering teams - building production agents and retrieval-augmented applications, establishing the standards and reusable assets other teams build on, and evaluating the AI development platforms the organisation adopts. Three positions are open. About the Role This is a hands-on engineering role. You will design and ship agentic systems in Python, build retrieval-augmented applications that run in production under real load, and turn what works into reusable accelerators, templates and standards that other engineering teams adopt. You will also act as the subject matter expert for agentic and generative AI within the engineering organisation, guiding and mentoring teams as they take these practices on. Key Responsibilities - Build agentic systems - design and implement agents and autonomous workflows that run in production, including tool integration, failure handling, termination conditions and cost control. - Ship with AI-assisted development platforms - deliver production-quality software using AI-assisted development tooling, and set the practice for how it is used well. - Establish standards - establish, maintain and evolve standards, patterns, governance frameworks and best practices for AI-assisted software engineering. - Evaluate emerging tooling - assess new AI development tools, frameworks and platforms, and recommend enterprise adoption strategy. - Build reusable assets - develop accelerators, templates, prompt libraries and enablement assets that improve engineering productivity and consistency. - Act as subject matter expert - serve as the SME for agentic development, generative AI and AI-powered software delivery, providing guidance and mentorship across teams. Required Skills & Experience - Python - strong production proficiency. Type Script/Java Script or Java accepted as a secondary language where your AI work was built in them. - Retrieval-Augmented Generation (RAG) - at least one RAG application you took to production and operated, not a prototype. - Agentic AI - hands-on design and implementation of agents and autonomous workflows with real users. You should be able to walk through tool integration, what failed, and how you bounded it. - Prompt engineering - applied prompt and context work as part of shipping systems. - Agent frameworks - working experience with any one of Lang Graph, Lang Chain, Auto Gen, CrewAI or Semantic Kernel. - AI-assisted development platforms - daily production use of Claude Code, Git Hub Copilot, Cursor, Windsurf or equivalent. - Engineering background - 5+ years total in software engineering, with roughly the last two years in the AI space. - Driving adoption - ability to take a practice across multiple teams, with evidence that teams actually adopted what you built. Nice-to-Have / Preferred - Reusable engineering assets - prompt libraries, templates, playbooks or accelerators adopted broadly across an organisation. - AI governance - governance frameworks, onboarding guides, training materials or operational processes for AI-assisted software engineering. - Model Context Protocol (MCP) - familiarity with MCP and enterprise orchestration patterns. - Multi-agent architecture - experience coordinating multiple agents. - Autonomous coding agents - exposure to Devin or equivalent. - Financial services exposure - BFSI or capital markets background advantageous. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.