Cloud/AI Engineer

Strategic Innovation Group, LLC is a government contractor providing technical expertise in digital transformation, data management, data science, and systems modernization. The Cloud/AI Engineer will lead the design, development, deployment, and sustainment of secure cloud-native and artificial intelligence solutions supporting Federal Aviation Administration programs. The role focuses on cloud modernization, production-grade AI and Generative AI applications, technical leadership, security, compliance, and collaboration with government stakeholders and engineering teams.

Responsibilities:

• Lead the design, development, deployment, and sustainment of secure, scalable cloud and AI solutions supporting FAA mission objectives
• Collaborate with government stakeholders to translate business requirements into innovative, mission-focused technology solutions
• Lead the modernization of legacy systems and enterprise platforms through cloud transformation and application modernization initiatives
• Establish and promote architecture, engineering, security, and software development best practices across project teams
• Provide technical leadership, mentoring, and guidance to engineering teams while supporting Agile project delivery
• Ensure solutions meet federal security, governance, compliance, and operational requirements throughout the system lifecycle
• Develop and maintain technical documentation, architecture artifacts, and implementation plans to support operations and compliance
• Evaluate emerging technologies, resolve complex technical challenges, and recommend improvements that enhance performance, reliability, and mission outcomes
• Perform other duties as assigned

Requirements:

• Must have 15+ year experience with Bachler's and 13+ years experience with Master's
• Bachelor's degree in Computer Science, Engineering, or a related technical field
• Cloud Engineer experience: 15+ years
• AI Engineer experience: 1+ years
• Experience delivering enterprise-scale technology solutions across public-sector and private-sector organizations, including highly ambiguous environments requiring problem discovery, requirements definition, and solution development
• Hands-on experience in cloud engineering, cloud-based application development, and full stack software engineering
• Proven track record designing, building, deploying, and operating production-grade applications spanning front-end interfaces, backend services, and cloud data platforms
• Experience migrating legacy on-premises systems to the cloud and refactoring monolithic legacy codebases into microservices architectures and cloud-native tooling, using Docker, Kubernetes, serverless services, and cloud platforms such as AWS, Azure, or Google Cloud
• Experience leading or executing migrations from on-premises data warehouses to cloud-based data warehouse platforms (e.g., Snowflake, Amazon Redshift, Google BigQuery, Azure Synapse), including data pipeline redesign, schema conversion, and validation of data integrity throughout the migration
• Strong proficiency in Python, JavaScript/TypeScript, React, FastAPI, SQL, Spark/PySpark, REST APIs, and modern software development frameworks
• Expertise implementing CI/CD pipelines, DevOps practices, infrastructure automation (e.g., Terraform, CloudFormation), and platform engineering principles to support scalable cloud delivery
• Experience integrating enterprise systems through APIs, event-driven architectures, workflow orchestration platforms, and distributed services
• Strong understanding of software engineering fundamentals, distributed systems, cloud architecture, and cloud application engineering best practices
• Demonstrated ability to architect secure, scalable, and resilient cloud systems with attention to governance, auditability, data protection, and access controls
• Hands-on experience developing and deploying Generative AI solutions, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI systems, semantic search, and vector databases, integrated into cloud-native application architectures
• Experience managing the AI application lifecycle within cloud environments, including data ingestion, model integration, deployment, monitoring, observability, and continuous improvement using cloud-native MLOps tooling
• Proven ability to collaborate with business stakeholders, product teams, and technical leadership to translate business requirements into scalable technical solutions and AI-enabled products
• Experience delivering mission-critical applications in regulated, compliance-sensitive, or enterprise environments
• Strong analytical, problem-solving, and systems-thinking skills with the ability to identify operational challenges and develop technology solutions that deliver measurable business value
• Must have ability to obtain a Public Trust clearance
• Prior experience in federal contracting or highly regulated enterprise environments
• Active FAA clearance