Senior AI Engineer Artificial Intelligence

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 pod teammates contributing to the 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 work hands-on with large language models, RAG pipelines, agentic frameworks, and the MEAN/MERN stack gaining practical depth across the full AI product engineering lifecycle while working on high-impact client engagements across diverse industries.

What You will do:

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 and practice eval driven development, ensuring output quality and consistency across releases.
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.
Communicate workstream outcomes clearly and consistently to internal stakeholders, and actively participate in cross-functional working sessions.

Ideally, you have:

Undergraduate degree (B.E./B.Tech.) in Computer Science, Information Technology, or a related engineering discipline; candidates from tier-1 or tier-2 institutions are preferred.
2-4 years of overall software development experience, with a demonstrable track record of building and delivering production-grade applications.
A minimum of 1 year of hands-on experience developing Generative AI applications including LLM integration, RAG pipeline development, and prompt engineering; equivalent depth through projects or academic work will be considered, given the emerging nature of the field.
Practical experience integrating large language models into applications, including prompt engineering, tool use, and evaluation design.
Working knowledge of AI orchestration and agent frameworks, and core RAG principles including chunking strategies, embedding models, and experience with vector databases and semantic retrieval pipelines.
Experience with LangChain, LangGraph, AutoGen, DSPy, or equivalent orchestration frameworks.
Hands-on experience with the MERN or MEAN stack MongoDB, Express.js, React.js or Angular, Node.js supported by at least one end-to-end deployed project.
Proficiency in Python and SQL for data querying; working knowledge of JavaScript/TypeScript for full-stack development.
Working knowledge of version control and collaborative development workflows using Git and GitHub or GitLab, including branching strategies and pull request reviews; experience with CI/CD pipelines.
Basic familiarity with cloud platforms such as AWS or Azure and containerization using Docker.
Strong grasp of evaluation methodologies: designing evals, catching regressions, assessing LLM output quality.
Comfortable using AI productivity tools daily to accelerate research, writing, and coding tasks; candidates should be able to demonstrate tangible productivity gains from their use.
Strong written and verbal communication skills; able to produce clear tickets, user stories, and concise technical documentation.
Strong learning agility and the ability to operate effectively in a collaborative, sprint-driven delivery environment with high client expectations.
Familiarity with enterprise business applications and workflows is advantageous; domain knowledge in any industry vertical will be viewed favorably.

Disclaimer : This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

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