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Company overview Accordion is a global financial consulting and technology firm helping CFOs and their teams drive value creation. Rooted in private equity rigor and powered by data, analytics, and AI, we partner with companies across industries to turn insight into impact. Accordion works at the intersection of Private Equity sponsors and portfolio companies' management teams across every stage of the investment lifecycle. We provide hands-on, execution-oriented support, driving value through the office of the CFO by building data and analytics capabilities and identifying and implementing strategic work, rooted in data, analytics and AI. Accordion is headquartered in New York City with 10 offices worldwide, including the India office based out of Hyderabad. Join us and make your mark on our company. Data & Analytics Accordion's Data & Analytics (D&A) practice in India delivers cutting-edge, intelligent solutions to a global clientele, leveraging a blend of domain knowledge, sophisticated technology tools, and deep analytics capabilities to tackle complex business challenges. We partner with Private Equity clients and their Portfolio Companies across diverse sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics. D&A team members deliver data and analytical solutions designed to streamline reporting capabilities and enhance business insights across vast and complex data sets ranging from Sales, Operations, Marketing, Pricing, Customer Strategies, and more. Working at Accordion in India means joining 800+ analytics, data science, finance, and technology experts in a high-growth, agile, and entrepreneurial environment to transform how portfolio companies drive value. It also means making your mark on Accordion's futureby embracing a culture rooted in collaboration and a firm-wide commitment to building something great, together. Join us and experience a better way to work! Location: Hyderabad, Telangana Role Overview Accordion is looking for experienced AI Engineers to join our new AI-augmented delivery pods: purpose-built teams that combine AI engineering, data science, and product management to transform how PE-backed companies run finance and operations. You will work with clients and cross-functional delivery pod teammates contributing to the design, development and maintenance of AI solutions that address complex business challenges for clients globally and continuously raise the bar on what AI-assisted delivery looks like. In this role, you will be actively involved in AI solution architecture design, work hands-on with large language models, RAG pipelines, and multi-agent frameworks, contribute across the MEAN/MERN stack and guide a team of Associates gaining practical depth across the full AI product engineering lifecycle, from discovery through production. What You will do: Propose AI solution architecture to ensure solutions are scalable, secure, and aligned with engineering standards Build and iterate on Generative AI features encompassing prompt engineering, RAG pipelines, and multi agent workflows using AI orchestration frameworks Integrate large language models into enterprise applications, ensuring reliable data flow and seamless compatibility with existing systems and data sources Develop prototypes and proof of concepts to validate AI solutions, iterating on models based on stakeholder feedback prior to full-scale implementation Write and execute regression evaluation suites for LLM-based features, ensuring output quality and consistency across releases Build observability and evaluation infrastructure to continuously improve production AI system quality Monitor AI pipelines and application components using observability platforms; proactively identify, investigate, and escalate issues before they impact delivery Develop and maintain web applications using the MEAN or MERN stack (MongoDB, Express.js, Angular or React.js, Node.js) on Azure and AWS platforms Write clean, well-structured, and testable code in Python and JavaScript/TypeScript, adhering to REST API design principles and established engineering standards Debug and resolve production issues within sprint timelines, documenting root cause analysis and resolution steps clearly Maintain technical documentation, API specifications, and CI/CD pipeline integrity Guide and mentor Associates within the pod, conducting code reviews, sharing knowledge, and supporting their technical development Write product requirement documents (PRDs), user stories, and functional specifications to translate engagement goals into clearly scoped development tasks Translate ambiguous client problems into engineering requirements and deliver results in compressed timeframes Present and defend architectural decisions to technical and non-technical audiences Lead sprint ceremonies planning, standups, and retrospectives ensuring pod velocity is maintained and blockers are surfaced and resolved promptly Drive .
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.