Lead Full Stack Developer

Description
JOB DESCRIPTION
Michael Baker International is seeking a highly skilled Lead Full Stack Developer with deep AI/ML expertise to architect, build, and scale intelligent, data-driven applications across our enterprise ecosystem. This role combines strong hands-on engineering capabilities with technical leadership, guiding cross-functional teams in delivering modern, scalable, and AI-enhanced digital experiences. This role will collaborate on efforts to advance automation, middleware integration, and developer experience improvements, supporting innovation through emerging technologies for distributed AI workloads.

Responsibilities
Technical Leadership

• Lead end-to-end architecture, design, and development of full-stack applications with AI/ML components.
• Drive best practices in coding, scalability, security, CI/CD, and cloud-native development.
• Coach and mentor developers, data engineers, and ML engineers.
• Own solution design reviews, technical roadmaps, and architectural decisions.

Full-Stack Development

• Develop high-performance front-end interfaces using modern frameworks (React, , Angular, Vue).
• Architect secure, scalable backend services using , Python, Go, or Java.
• Build RESTful and GraphQL APIs.
• Implement testing, code quality pipelines, and DevOps workflows.
• Integrate real-time data streams for AI-driven features.
• Leverage enterprise frameworks (.NET 8, ASP.NET Core) and cloud-native orchestration (Azure AKS, Kubernetes, Helm) for scalable AI deployments.
• Incorporate MCP servers and distributed compute frameworks to support large-scale AI/ML inference and training.

AI/ML Engineering

• Productionize ML models and integrate them into real-world applications.
• Build ML-driven features such as recommendation engines, anomaly detection, and NLP.
• Design data pipelines, feature stores, vector databases, and inference layers.
• Optimize model performance and deployment strategies.
• Implement model drift detection, automated retraining pipelines, and AI observability frameworks.
• Research and prototype emerging AI technologies (LLMs, GenAI, RAG architectures).
• Ensure responsible and ethical AI deployment practices.
• Explore advanced AI applications such as digital twins and immersive analytics to accelerate innovation.

Cloud, Data, and DevOps

• Lead cloud architecture (AWS, Azure, GCP) with serverless and containerization.
• Implement CI/CD pipelines.
• Ensure strong security posture aligned with Zero Trust and SOC2.
• Support observability, monitoring, and data governance.

Execution Champion

• Define and execute enterprise AI/ML strategies aligned with key business outcomes.
• Champion best practices in data engineering, MLOps, and cloud optimization.
• Champion AI governance, compliance, and ethical AI principles across all solutions.
• Promote cross-functional AI adoption and educate stakeholders on AI capabilities and limitations.

Team Development and Stakeholder Engagement

• Lead and mentor AI/ML engineering teams.
• Collaborate with data scientists, ML engineers, and business stakeholders to deliver impactful solutions.
• Translate business requirements into scalable AI/ML strategies.

Professional Requirements

• Bachelor's degree in Computer Science or related field, or similar, or equivalent experience.
• Any 8+ years of full-stack engineering experience.
• Expertise in JavaScript/TypeScript, Python, and modern front-end frameworks.
• Strong AI/ML experience with TensorFlow, PyTorch, Scikit-Learn, or similar.
• Experience deploying ML models and integrating AI features into applications.
• Proficiency in microservices, distributed systems, and cloud platforms.
• Strong SQL/NoSQL experience and API design skills.
• Experience with enterprise-grade frameworks (.NET 8, ASP.NET Core) and cloud-native orchestration across Azure, AWS, and GCP, including Kubernetes and Helm.
• Knowledge of identity and security frameworks (OAuth 2.0, OIDC).
• Familiarity with MCP servers and distributed compute frameworks for AI scalability.
• Data or AI/ML related certifications.

Preferred Qualifications

• Experience with GenAI, LLMs, vector search, RAG architectures.
• Experience with MLOps tools (Kubeflow, MLFlow, SageMaker).
• Real-time data frameworks (Kafka, Spark).
• Prior experience in regulated industries.
• Open-source contributions.
• Strong problem-solving and systems-thinking abilities.
• Ability to lead cross-functional teams.
• Excellent communication skills.
• Passion for innovation and continuous learning

Compensation
The approximate compensation range for this position is $130,000 to $170,000. This compensation range is a good-faith estimate for the position at the time of posting. Actual compensation is dependent upon factors such as education, qualifications, experience, skillset, and physical work location.

Benefits
We offer a comprehensive benefits package including:

• Medical, dental, vision insurance
• 401 (k) Retirement Plan
• Health Savings