Software Engineer IV - AI

SEA CORP

Location:

Middletown, RI, United States Req ID:

req1880 SEACORP is seeking a well-qualified Software Engineer IV - AI .

Primary Duties and Responsibilities:

Job Summary :

SEACORP is seeking to fill a Software Engineer - AI positionto support the development, integration, testing, and sustainment of modern USNavy software systems using advanced AI-assisted software engineeringworkflows. This position is intended for highly capable software engineers whoare proficient not only in software development fundamentals, but also inleveraging AI-enabled development tools to accelerate delivery, improve codequality, automate repetitive tasks, and enhance engineering productivity acrossthe software lifecycle. The ideal candidate understands how to effectively utilizeAI coding assistants, agentic software engineering workflows, and moderndeveloper tooling to support requirements analysis, software implementation,testing, debugging, refactoring, documentation generation, and codebasecomprehension. This role requires strong engineering judgment and the abilityto balance AI-generated outputs with sound software engineering principles,architecture awareness, maintainability, and operational reliability.

Job Responsibilities Include:

Develop, integrate, test, and maintain software applications using modern AI-assisted software engineering workflows. Utilize AI development tools such as Cursor, Claude Code, OpenAI Codex, Continue.dev, and related technologies to improve software engineering productivity and effectiveness. Collaborate with software engineers, architects, testers, and system integrators within Agile software development environments. Implement software solutions in Java and related technologies while applying secure coding practices and software engineering best practices. Utilize Git, GitLab, and Atlassian collaboration tools to support source control, issue tracking, code reviews, sprint execution, and software delivery workflows. Support AI-assisted code generation, debugging, test generation, refactoring, and documentation activities while validating outputs for correctness, maintainability, and security. Work within large and complex codebases while leveraging AI tooling to improve software comprehension, navigation, and development efficiency. Support CI/CD-driven software engineering workflows and automated testing approaches. Assist with the evaluation and adoption of emerging AI-enabled software engineering tools, workflows, and developer productivity technologies. Produce technical documentation, software artifacts, test evidence, and implementation guidance to support engineering and program objectives.

Qualifications:

Education:

Bachelor'sdegree in Computer Science, Software Engineering, Computer Engineering, InformationSystems, or a related technical field.

Experience:

Requiredknowledge of Git, GitLab, Atlassian tools, VS Code, Cursor, Java, Claude Code,OpenAI Codex, Continue.dev, Linux, and Red Hat Enterprise Linux (RHEL).Candidates should have the ability to work in a fast-paced work environment.

Able to collaborate with others while being able to handle independent tasking.

Ability to learn new technologies quickly.

Required Experience:

Requiredknowledge of Git, GitLab, Atlassian tools, VS Code, Cursor, Java, Claude Code,OpenAI Codex, Continue.dev, Linux, and Red Hat Enterprise Linux (RHEL).Candidates should have the ability to work in a fast-paced work environment.

Able to collaborate with others while being able to handle independent tasking.

Ability to learn new technologies quickly. 3+ years of experience in software engineering, software integration, or application development. Experience using AI-assisted software engineering tools and workflows to support software development activities. Strong experience with Git-based development workflows and collaborative source control practices. Experience with GitLab repositories, merge requests, branching strategies, and CI/CD integration workflows. Experience utilizing Atlassian tools such as Jira and Confluence within Agile software development environments. Strong proficiency with modern software development environments including VS Code and AI-enabled development extensions. Experience developing software applications in Java. Experience working within Linux-based development and deployment environments, including Red Hat Enterprise Linux (RHEL). Familiarity with Linux command-line operations, shell scripting, package management, system services, permissions, process management, and development toolchains. Ability to evaluate, validate, and refine AI-generated code outputs for correctness, security, maintainability, and operational suitability. Experience troubleshooting software defects, integration issues, build/test failures, and Linux-based runtime issues.

Desired Experience:

Desired knowledge in theareas of AI-enabled software engineering workflows, agentic softwaredevelopment, embeddings generation, context optimization for large codebases,modern developer productivity tooling, and Linux-based software environments. Master's degree in Computer Science, Software Engineering, or a related discipline. Experience with Team Submarine, SWFTS, US Navy program offices, TI/APB cycle Experience generating and utilizing embeddings to improve software engineering workflows, semantic search, retrieval augmentation, or codebase understanding. Experience reducing context complexity and optimizing workflows for large software repositories and multi-project codebases. Experience developing software in C++, Python, Go, or Rust. Familiarity with containerized Linux development environments, Docker, Kubernetes, or DevOps workflows. Familiarity with LLM orchestration frameworks, MCP-based integrations, or agentic development environments. Experience with AI-assisted test generation, code review automation, or software documentation generation. Experience supporting software development within defense, government, or mission-critical environments. Experience with OpenClaw and Claude Cowork.

Exceptional Qualifications:

Candidatespossessing knowledge in these technologies will be considered exceptionalcandidates: Deep expertise utilizing AI-assisted software engineering workflows to accelerate software delivery while maintaining engineering rigor and code quality. Demonstrated experience integrating multiple AI coding assistants and developer productivity tools into production engineering workflows. Experience improving developer productivity across large-scale software repositories through embeddings, retrieval augmentation, semantic indexing, or context optimization techniques. Experience developing or integrating autonomous or semi-autonomous software engineering agents. Demonstrated ability to balance AI-generated implementation approaches with sound architecture, software quality, cybersecurity, and long-term maintainability considerations. Deep familiarity with the Hugging Face ecosystem including Transformers, Datasets, Tokenizers, PEFT, TRL, Accelerate, Diffusers, Safetensors, Text Generation Inference (TGI), and model packaging workflows. Experience with LangChain, LangGraph, LlamaIndex, Semantic Kernel, DSPy, AutoGen, CrewAI, OpenAI SDKs/APIs, Anthropic APIs, Ollama APIs, vLLM APIs, LiteLLM, and MCP-based integrations. Experience integrating AI/ML capabilities into production software applications, APIs, developer platforms, CI/CD pipelines, IDE tooling, or enterprise software systems. Experience designing Retrieval-Augmented Generation (RAG) pipelines including embeddings generation, vectorization strategies, semantic chunking, reranking, hybrid search, and contextual retrieval techniques. Experience with vector databases and semantic search technologies such as FAISS, ChromaDB, Milvus, Weaviate, Pinecone, Elasticsearch/OpenSearch vector search, pgvector, or Qdrant. Experience with local or enterprise model inference hosting technologies including vLLM, Ollama, Hugging Face TGI, TensorRT-LLM, llama.cpp, Triton Inference Server, Ray Serve, BentoML, or KServe. Experience deploying and operating AI inference workloads on Kubernetes, Docker, Podman, OpenShift, or cloud-native GPU-enabled environments. Experience with distributed AI/ML training technologies including PyTorch Distributed, DeepSpeed, FSDP, Megatron-LM, Ray, Horovod, or NVIDIA NeMo. Experience developing, fine-tuning, training, evaluating, deploying, and hosting Large Language Models (LLMs) and AI/ML models in enterprise or on-premise environments. Experience with model optimization techniques including quantization, LoRA/QLoRA fine-tuning, pruning, batching optimization, speculative decoding, caching strategies, and GPU memory optimization. Experience with GPU-enabled infrastructure including NVIDIA CUDA, Tensor

RT, NCCL, MIG

partitioning, multi-GPU orchestration, and high-performance AI compute environments. Experience with AI observability, evaluation, and monitoring technologies such as LangSmith, Weights & Biases, MLflow, OpenTelemetry, Phoenix/Arize, TruLens, or prompt evaluation frameworks. Experience with AI security and governance technologies including model isolation, prompt injection protections, content filtering, secrets management, supply chain validation, and secure model deployment practices. Experience building AI-enabled developer tooling including AI copilots, code assistants, autonomous coding agents, semantic code search, AI-driven test generation, or AI-enabled software modernization tools. Experience working with modern data and AI pipelines using Apache Kafka, Spark, Iceberg, Airflow, Ray, Redis, or streaming data architectures supporting AI/ML applications. Experience with enterprise AI deployment in disconnected, air-gapped, regulated, or classified environments. As a requirement of em ployment, all SEACORP employees must hold U.S. Citizenship.

Location:

Middletown, RI Travel:

Quarterly (approximately 4 times a year)

Clearance:

Secret Work Environment & Physical Demands:

Office & Computer Laboratories - Sitting, standing, extended periods of time using a mouse and keyboard and viewing computer screens. Infrequent lifting of