Trainee Github Software Engineer Jobs in Alabama

Igniters operate in the world's most demanding environment. Igniters are self-motivated, mission-driven, and relentless in solving the Warfighters' hardest problems. We move fast, think differently, and execute with precision to tackle high-stakes challenges across AI/ML, space and missile defense intelligence, EMSO, advanced analytics, and programmatic domains.

As an employee-owned SDVOSB headquartered in Huntsville, AL, our team delivers mission-critical impact for the Army, Air Force, Space Force, MDA, NASA, DIA, and FBI. Ignite exists to outpace the threat and deliver results that matter in the moments that count. Ignite is hiring an AI/ML Software Engineer in Huntsville, AL.

This is a hands-on engineering position suited for early-career professionals who are eager to grow technically in a fast-moving environment. The employee will work within a dedicated AI and Automation team and collaborate closely with cross-functional teams spanning Software Development, Data Analytics, and Infrastructure, contributing meaningfully to architecture decisions, development work, and deployment operations from day one. The ideal candidate brings a strong foundation in AI/ML concepts, modern software development practices, and the adaptability to work across frontend, backend, and infrastructure as needed.Responsibilities AI/ML Development and Integration Develop and integrate AI/ML capabilities into mission-focused web applications, including large language model (LLM) integration, retrieval-augmented generation (RAG) pipelines, and intelligent automation workflows Assist in the design and implementation of data ingestion, embedding, vector search, and model serving pipelines Support prompt engineering, model evaluation, and performance tuning for deployed AI features Research and prototype emerging AI/ML tools, frameworks, and techniques to identify opportunities for mission improvement Support the design and development of agentic AI systems, including autonomous agents capable of multi-step planning, tool use, and orchestrated task execution within mission workflows Full-Stack Application Development Build and maintain web application features using modern frontend frameworks (e.g., React, TypeScript) and backend frameworks (e.g., Python, FastAPI) Design and implement RESTful APIs and contribute to database design and query optimization (e.g., PostgreSQL) Write clean, testable, and well-documented code following team coding standards and established design patterns Participate in code reviews, sprint planning, and collaborative development within an Agile workflow CI/CD and DevSecOps Contribute to the development and maintenance of CI/CD pipelines for automated testing, security scanning, and deployment Support containerized application builds and deployments using Docker and container orchestration platforms (e.g., Kubernetes) Assist with static application security testing (SAST) integration and remediation of findings within the development pipeline Help maintain and improve infrastructure-as-code configurations and deployment automation scripts Collaboration and Communication Collaborate with the AI and Automation team to plan, estimate, and deliver work in iterative development cycles Document technical designs, implementation decisions, and operational procedures for team and stakeholder reference Support demonstrations, briefings, and technical reviews for program leadership and government stakeholders Required Qualifications Education Bachelor's degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, or a closely related technical field Experience Professional experience in software development, AI/ML engineering, or a related technical role (internship and academic project experience considered) Technical Skills Proficiency in Python and at least one modern web development language or framework (e.g., JavaScript/TypeScript, React) Foundational understanding of AI/ML concepts, including natural language processing (NLP), large language models (LLMs), embeddings, and vector search Experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and RESTful API design Familiarity with version control systems (Git) and collaborative development workflows (branching strategies, merge requests, code reviews) Basic understanding of containerization (Docker) and container orchestration concepts (Kubernetes) Familiarity with CI/CD pipeline concepts and at least one CI/CD platform (e.g., GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins) Exposure to at least one cloud platform (AWS, Microsoft Azure, or Google Cloud) and general understanding of cloud-native application architecture Security Clearance Active Secret security clearance Certification Must obtain CompTIA Security+ certification (or equivalent DoD 8570/8140 baseline certification) within 30 days of start date Work Environment On-site position at a U.S

government facility in Huntsville, AL Small, collaborative team environment with direct mentorship from senior engineers Opportunity to contribute to meaningful mission outcomes through hands-on engineering of AI-driven solutions Fast-paced environment where you will be encouraged to learn, experiment, and grow your technical capabilities Preferred Qualifications Education Bachelor's degree with a concentration or specialization in Artificial Intelligence or Machine Learning Relevant graduate coursework or a Master's degree in AI/ML, Computer Science, or a related field Experience and Skills Experience building or contributing to RAG (retrieval-augmented generation) architectures or LLM-powered applications Hands-on experience with AI/ML frameworks and libraries such as LangChain, LlamaIndex, Hugging Face Transformers, PyTorch, or TensorFlow Exposure to agentic AI concepts and frameworks, including multi-agent orchestration, tool-use patterns, and autonomous task execution (e.g., LangGraph, CrewAI, AutoGen, or similar) Experience with FastAPI, Flask, or Django for building backend services Experience with React, Next.js, or similar component-based frontend frameworks and UI libraries (e.g., Material UI) Familiarity with SAST tools (e.g., Semgrep, SonarQube, Bandit) and secure software development practices Experience with Kubernetes (e.g., GKE, EKS, AKS) in a development or deployment capacity Exposure to infrastructure-as-code tools (e.g., Terraform, Helm) or GitOps workflows Experience developing or deploying applications within U.S. government or Department of Defense IT environments Familiarity with FedRAMP, IL4/IL5, or CMEK compliance concepts in cloud environments Certifications (any of the following are a plus) AWS Certified Machine Learning - Specialty or AWS Certified Solutions Architect - Associate Google Cloud Professional Machine Learning Engineer or Google Cloud Associate Cloud Engineer Microsoft Certified: Azure AI Engineer Associate or Azure Developer AssociateResponsibilities AI/ML Development and Integration Develop and integrate AI/ML capabilities into mission-focused web applications, including large language model (LLM) integration, retrieval-augmented generation (RAG) pipelines, and intelligent automation workflows Assist in the design and implementation of data ingestion, embedding, vector search, and model serving pipelines Support prompt engineering, model evaluation, and performance tuning for deployed AI features Research and prototype emerging AI/ML tools, frameworks, and techniques to identify opportunities for mission improvement Support the design and development of agentic AI systems, including autonomous agents capable of multi-step planning, tool use, and orchestrated task execution within mission workflows Full-Stack Application Development Build and maintain web application features using modern frontend frameworks (e.g., React, TypeScript) and backend frameworks (e.g., Python, FastAPI) Design and implement RESTful APIs and contribute to database design and query optimization (e.g., PostgreSQL) Write clean, testable, and well-documented code following team coding standards and established design patterns Participate in code reviews, sprint planning, and collaborative development within an Agile workflow CI/CD and DevSecOps Contribute to the development and maintenance of CI/CD pipelines for automated testing, security scanning, and deployment Support containerized application builds and deployments using Docker and container orchestration platforms (e.g., Kubernetes) Assist with static application security testing (SAST) integration and remediation of findings within the development pipeline Help maintain and improve infrastructure-as-code configurations and deployment automation scripts Collaboration and Communication Collaborate with the AI and Automation team to plan, estimate, and deliver work in iterative development cycles Document technical designs, implementation decisions, and operational procedures for team and stakeholder reference Support demonstrations, briefings, and technical reviews for program leadership and government stakeholders Required Qualifications Education Bachelor's degree in Artificial Intelligence, Machine Learning, Computer Science, Data Science, Software Engineering, or a closely related technical field Experience Professional experience in software development, AI/ML engineering, or a related technical role (internship and academic project experience considered) Technical Skills Proficiency in Python and at least one modern web development language or framework (e.g., JavaScript/TypeScript, React) Foundational understanding of AI/ML concepts, including natural language processing (NLP), large language models (LLMs), embeddings, and vector search Experience with relational databases (e.g., PostgreSQL, MySQL, SQL Server) and RESTful API design Familiarity with version control systems (Git) and collaborative development workflows (branching strategies, merge requests, code reviews) Basic understanding of containerization (Docker) and container orchestration concepts (Kubernetes) Familiarity with CI/CD pipeline concepts and at least one CI/CD platform (e.g., GitLab CI/CD, GitHub Actions, Azure DevOps, Jenkins) Exposure to at least one cloud platform (AWS, Microsoft Azure, or Google Cloud) and general understanding of cloud-native application architecture Security Clearance Active Secret security clearance Certification Must obtain CompTIA Security+ certification (or equivalent DoD 8570/8140 baseline certification) within 30 days of start date Work Environment On-site position at a U.S. government facility in Huntsville, AL Small, collaborative team environment with direct mentorship from senior engineers Opportunity to contribute to meaningful mission outcomes through hands-on engineering of AI-driven solutions Fast-paced environment where you will be encouraged to learn, experiment, and grow your technical capabilities Preferred Qualifications Education Bachelor's degree with a concentration or specialization in Artificial Intelligence or Machine Learning Relevant graduate coursework or a Master's degree in AI/ML, Computer Science, or a related field Experience and Skills Experience building or contributing to RAG (retrieval-augmented generation) architectures or LLM-powered applications Hands-on experience with AI/ML frameworks and libraries such as LangChain, LlamaIndex, Hugging Face Transformers, PyTorch, or TensorFlow Exposure to agentic AI concepts and frameworks, including multi-agent orchestration, tool-use patterns, and autonomous task execution (e.g., LangGraph, CrewAI, AutoGen, or similar) Experience with FastAPI, Flask, or Django for building backend services Experience with React, Next.js, or similar component-based frontend frameworks and UI libraries (e.g., Material UI) Familiarity with SAST tools (e.g., Semgrep, SonarQube, Bandit) and secure software development practices Experience with Kubernetes (e.g., GKE, EKS, AKS) in a development or deployment capacity Exposure to infrastructure-as-code tools (e.g., Terraform, Helm) or GitOps workflows Experience developing or deploying applications within U.S

government or Department of Defense IT environments Familiarity with FedRAMP, IL4/IL5, or CMEK compliance concepts in cloud environments Certifications (any of the following are a plus) AWS Certified Machine Learning - Specialty or AWS Certified Solutions Architect - Associate Google Cloud Professional Machine Learning Engineer or Google Cloud Associate Cloud Engineer Microsoft Certified: Azure AI Engineer Associate or Azure Developer Associate