Senior Engineer Applied AI (Java)

Accellor • Chevy Chase, MD

20h

About The Position

Accellor is an AI-first digital transformation partner built for the next generation of enterprise. We help global organizations turn cloud, data, and AI into real, measurable business outcomes at scale. At Accellor, people come first . You’ll be trusted, empowered, and challenged to solve meaningful problems, collaborate with exceptional teams, and continuously grow your skills while building solutions that matter. Trusted by Fortune 100 companies and global innovators, we work across industries delivering AI solutions, data platforms, and product engineering using modern, scalable technologies. If you want your work to create real impact and shape the future of enterprise , Accellor is where it happens. Job Description Design, develop, and maintain scalable, high-performance microservices using Java (version 21+) and Spring Boot (3.4.x) to power AI-enabled applications. Contribute to the architecture and implementation of applied AI solutions across enterprise workflows including automation, document intelligence, decision support, and intelligent assistants. Build and integrate AI agents and agentic workflows that orchestrate tools, APIs, reasoning steps, and business logic using Java-based AI frameworks. Implement Retrieval-Augmented Generation (RAG) patterns, Model Context Protocol (MCP) integrations, and agent skills to enhance AI application capabilities. Develop systems that meet high standards for scalability, resilience, performance, and availability in production environments. Leverage knowledge graphs and vector databases to enhance reasoning, entity relationships, and context retrieval in AI workflows. Collaborate with product, engineering, operations, and analytics partners to translate business needs into technical designs and deliver scalable AI solutions. Participate in code reviews, provide constructive feedback, and help junior engineers develop AI and agentic workflow skills. Drive continuous improvement by exploring new models, frameworks, and reasoning techniques and applying them to real-world challenges. Utilize AI-assisted development tools (e.g., Claude, Cursor, Codex) to accelerate development and improve engineering productivity. Contribute to engineering best practices for reliability, interpretability, safety, governance, and monitoring of production AI systems.

Requirements

• Bachelor's or master's degree in computer science, Engineering, or a related technical field.
• 5+ years of professional software engineering experience building maintainable, scalable, and high-performance systems in Java.
• Strong proficiency in modern Java (preferably Java 21) with familiarity of recent features and best practices.
• Solid knowledge of Spring Boot (preferably 3.4.x+), Spring Cloud, and related frameworks.
• hands-on experience working with Generative AI, LLM-based systems, or AI-powered applications.
• Experience in designing and deploying distributed systems and microservice-based architectures.
• Understanding of AI concepts including agent architectures, RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol), and workflow orchestration.
• Experience using AI-assisted development tools (e.g., Claude, Cursor, Codex, or similar) to improve software engineering productivity.
• Strong understanding of RESTful API design, secure API development, and service-to-service communication patterns.
• Familiarity with cloud technologies (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
• Solid understanding of CI/CD, automated testing, and observability practices.
• Good communication skills and a collaborative, team-oriented mindset.
• Ability to collaborate across teams and co-create solutions with engineers, product managers, and domain experts.

Nice To Haves

• Experience deploying AI components in Java ecosystems including Spring AI, LangChain4j, or Embabel.
• Hands-on experience with Temporal or similar workflow orchestration frameworks.
• Experience with vector databases (Pinecone, Weaviate, Milvus, pgvector) and knowledge graph technologies.
• Familiarity with Python-based AI frameworks (LangChain, LlamaIndex, Hugging Face) for prototyping or integration.
• Experience with insurance, financial services, or other regulated industries.
• Background in document intelligence, fraud detection, or anomaly modeling.
• Experience mentoring junior engineers or leading small project initiatives.
• Contributions to open-source projects in AI, Java, microservices, or cloud tools.
• Familiarity with AI safety practices, evaluation frameworks, monitoring, and regulatory compliance.

Responsibilities

• Design, develop, and maintain scalable, high-performance microservices using Java (version 21+) and Spring Boot (3.4.x) to power AI-enabled applications.
• Contribute to the architecture and implementation of applied AI solutions across enterprise workflows including automation, document intelligence, decision support, and intelligent assistants.
• Build and integrate AI agents and agentic workflows that orchestrate tools, APIs, reasoning steps, and business logic using Java-based AI frameworks.
• Implement Retrieval-Augmented Generation (RAG) patterns, Model Context Protocol (MCP) integrations, and agent skills to enhance AI application capabilities.
• Develop systems that meet high standards for scalability, resilience, performance, and availability in production environments.
• Leverage knowledge graphs and vector databases to enhance reasoning, entity relationships, and context retrieval in AI workflows.
• Collaborate with product, engineering, operations, and analytics partners to translate business needs into technical designs and deliver scalable AI solutions.
• Participate in code reviews, provide constructive feedback, and help junior engineers develop AI and agentic workflow skills.
• Drive continuous improvement by exploring new models, frameworks, and reasoning techniques and applying them to real-world challenges.
• Utilize AI-assisted development tools (e.g., Claude, Cursor, Codex) to accelerate development and improve engineering productivity.
• Contribute to engineering best practices for reliability, interpretability, safety, governance, and monitoring of production AI systems.

Benefits

• Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being.
• Financial benefits including market-competitive compensation; a 401K savings plan, performance and recognition-based incentives; and tuition assistance.
• Access to additional benefits like mental healthcare as well as fertility and adoption assistance.
• Supports flexibility- We provide workplace flexibility as well as our Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level