Mid Level Ai Engineer

Capco; Massachusetts; Hybrid; USD 110,000 - 140,000; Full time

Benefits offered by this job

Medical, Dental, Vision coverage

401(k) with company match

Maternity/Paternity leave

Job summary

Capco is seeking a mid-level Generative AI Engineer to design, develop, and deploy AI-powered solutions built on Large Language Models, RAG, and agent-based architectures. You will collaborate with software engineers, product managers, and AI specialists to deliver scalable, production-grade AI across Capco’s financial services clients.

In this role, you’ll design AI-powered applications, optimize RAG pipelines with vector databases, and create intelligent agents that interact with APIs and

Qualifications

• 2–3 years of professional software/AI engineering experience.
• Hands-on experience with Generative AI tech, LLMs, and leading providers (OpenAI, Anthropic, Gemini, Azure OpenAI).
• Strong Python development with REST APIs, microservices, and scalable backends.

Responsibilities

• Design, build, and deploy AI-powered applications with LLMs and modern Generative AI frameworks.
• Develop and optimize RAG solutions using vector databases and enterprise data sources.
• Create intelligent AI agents/workflows interfacing with APIs and business systems.
• Build scalable REST APIs, backend services, and cloud-native architectures.
• Collaborate with cross-functional teams to translate requirements into production-ready AI solutions.

Skills

Generative AI

LLMs

Python

REST APIs

Microservices

Git

CI/CD

Cloud platforms

RAG architectures

Vector databases

Tools

Pinecone

Weaviate

Chroma

Qdrant

FAISS

Docker

Kubernetes

Job description

Mid Level AI Engineer

Location: Orlando, FL, USA (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent

Build the next generation of AI-powered solutions using Large Language Models, agentic systems, and cutting-edge Generative AI technologies.

The Role

Capco is seeking a Generative AI Engineer to help design, develop, and deploy intelligent applications powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based architectures. You will work alongside software engineers, product managers, and AI specialists to deliver scalable, production-grade AI solutions that solve complex business challenges and create exceptional user experiences.

This is an exciting opportunity to join a fast-growing AI capability, working on innovative solutions that transform how organizations leverage Generative AI technologies.

What You’ll Do

• Design, build, and deploy AI-powered applications using Large Language Models, foundation models, and modern Generative AI frameworks.
• Develop and optimize Retrieval-Augmented Generation (RAG) solutions leveraging vector databases and enterprise knowledge sources.
• Create intelligent AI agents and workflows capable of interacting with APIs, external tools, and business systems.
• Build scalable REST APIs, backend services, and cloud-native architectures to support AI-powered products.
• Collaborate with cross-functional teams to translate business requirements into robust, production-ready AI solutions.

What We’re Looking For

• 2–3 years of professional software; AI engineering experience.
• Hands-on experience building applications using Generative AI technologies, Large Language Models, and leading LLM providers such as OpenAI, Anthropic, Gemini, Azure OpenAI, or open-source models.
• Strong Python development skills with experience building REST APIs, microservices, and scalable backend applications.
• Practical experience implementing RAG architectures using vector databases such as Pinecone, Weaviate, Chroma, Qdrant, or FAISS.
• Understanding of software engineering best practices including Git, CI/CD, testing, code reviews, and cloud platforms such as AWS, Azure, or Google Cloud.

Bonus Points For

• Experience building multi-agent AI systems using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies.
• Familiarity with Model Context Protocol (MCP) and emerging agent interoperability standards.
• Experience with LLM observability and evaluation platforms such as LangSmith, Langfuse, Arize, or similar tools.
• Experience deploying containerized applications using Docker and Kubernetes.
• Exposure to frontend technologies such as React, TypeScript, modern web frameworks, or contributions to open-source AI projects.

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions.
• Work in a collaborative, flat, and entrepreneurial consulting culture.
• Access continuous learning, training, and industry certifications.
• Be part of a team shaping the future of digital financial services.
• Help shape the future of digital transformation across FS & Energy.

Benefits

• Medical, Dental, and Vision coverage.
• 401(k) with company match.
• Maternity and paternity leave, plus dependent care support.
• Tuition reimbursement, wellness reimbursement, HSA and FSA options.
• Commuter benefits and access to the Working Advantage employee discount marketplace.

Inclusion at Capco

We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

Use of Artificial Intelligence in Talent Acquisition

At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

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