Java Full Stack Backend Developer Jobs in Buffalo, NY

Senior Software Engineer (AI/ML)

Location: Remote-friendly; preference for candidates within commuting distance of Buffalo, NY for occasional in-person collaboration. Travel may be required for industry events or strategic meetings.

Company Overview

CoachMePlus is a leading provider of Human Performance solutions, empowering organizations and professionals to optimize physical readiness, mental resilience, and overall performance. Trusted by professional sports teams, tactical units, the US Army, youth academies, and wellness clinics, our platform is built to turn health and performance data into action.

Position Overview

CoachMePlus is now hiring a full-stack Senior AI/ML Software Engineer to join our team in support of an exciting Department of War human performance platform product support initiative. The position will require a government security clearance to be processed, so US or Naturalized Citizenship is a requirement for consideration.

In this role, the Senior Engineer will leverage expertise in cloud-native solutions and modern web architectures to lead the integration of cutting-edge Artificial Intelligence (AI) and Machine Learning (ML) capabilities into our product suite.

The ideal candidate will combine strong traditional software engineering foundations (such as the PHP ecosystem, legacy/modern JavaScript frameworks, and robust CI/CD practices) with hands-on experience deploying generative AI models and intelligent orchestration workflows. This role is primarily focused on AI/ML integration and supporting backend software development, though full stack development experience is preferred.

Key Responsibilities AI/ML & Cloud Integration

• Architect and deploy intelligent features using Cloud AI services, with a strong focus on building generative AI workflows, retrieval-augmented generation (RAG), and agentic pipelines.
• Develop serverless backends (e.g., AWS Lambda, API Gateway) and microservices that interface seamlessly with foundational machine learning models.
• Optimize data ingestion pipelines and database queries (SQL and NoSQL) to support context-rich AI prompts and high-performance inference.

DevOps & Architecture

• Set up, maintain, and secure automated CI/CD pipelines using Jenkins CI or similar cloud-native tooling to support continuous deployment of both software and ML integrations.
• Define technical requirements, break down tasks for complex engineering projects, and mentor junior developers on enterprise best practices.
• Consolidate legacy processes and automate critical workflows to drastically reduce manual business workloads and cycle times.

Full-Stack Web Development

• Incorporate AI-driven features (such as predictive text, intelligent search, automated categorization, or voice interfaces) directly into user-facing web and mobile frontends to improve user experience.
• Integrate AI/ML capabilities into existing PHP backend API.
• Write and implement software tooling to develop a new build pipeline in parallel with existing legacy tools.
• Provide thought leadership to architecture, design, and modernization approaches and activities. Contribute to architecture decisions and long-term technical roadmap.
• Organize work plans, estimate tasks, and deliver finished projects to meet important deadlines.

Qualifications Core Engineering Requirements

• Experience: 8–10 years of professional software development experience.
• Frontend: React, React Native, Polymer, JavaScript, HTML5, CSS3.
• Backend & Services: Strong proficiency in PHP 8.x (Symfony) and RESTful APIs, MySQL
• Cloud & DevOps: Deep familiarity with AWS (EC2, RDS, S3, Lambda, API Gateway, Cognito, DynamoDB), Infrastructure-as-Code tools (Terraform), Git SCM and Jenkins CI.
• Security: Familiarity and experience working in secure environments, particularly those constrained by federal and/or Department of War cybersecurity requirements.

AI/ML Requirements & Preferences

• AI Integration: Demonstrated experience consuming, fine-tuning, or orchestrating Large Language Models (LLMs) within enterprise applications.
• AWS Bedrock (Preferred): Knowledge of AWS Bedrock is highly preferred, specifically utilizing its API to manage foundation models, implement Guardrails, or build agents.
• Data Pipelines: Experience managing vector embeddings, prompt engineering, or working with cloud-native NoSQL data stores for AI context management.

Compensation & Benefits

• Salary Range: $150,000 – $175,000 annually
• Benefits Include:
  • Health insurance
  • Paid time off
  • Flexible work schedule
  • Parental leave
  • Professional development support
  • Work-from-home flexibility