Software Gigs

Staff Software Engineer role designing and implementing cloud-native platform components and services, with primary focus on Kubernetes workloads, distributed systems, and infrastructure automation. Requires 5+ years hands-on Kubernetes experience, proficiency in Go or systems languages, and demonstrated expertise building operators, controllers, and platform services. Will lead well-scoped projects from design through production, contribute to reliability and scalability, mentor junior engineers, and participate in on-call operations.

Senior Site Reliability Engineer responsible for designing and implementing Infrastructure as Code solutions, managing containerized and serverless architectures, and driving automation to reduce operational toil across large-scale production systems. The role requires defining Service Level Objectives (SLOs), leading incident response efforts, implementing monitoring and logging systems, and collaborating with development teams to ensure reliability and scalability. Requires 5+ years of SRE or cloud engineering experience with deep expertise in Terraform, CloudFormation, Docker, Kubernetes, CI/CD pipelines, and cloud security practices. Must be a US citizen eligible to obtain and maintain an active Secret security clearance or above.

This role involves evolving Qualcomm's Robotic Process Automation capabilities into next-generation agentic automation solutions. The Senior Agentic Automations Engineer will design and deploy AI-driven agents, enterprise chatbots, and workflow engines, leading technical delivery across a global team while integrating RPA platforms like Automation Anywhere with containerized architectures. Key responsibilities include defining automation standards, building full-stack enterprise applications, and ensuring secure integration with enterprise systems using Docker, Kubernetes, and agentic frameworks like LangGraph and n8n.

Design and implement Infrastructure as Code to automate provisioning, monitoring, and lifecycle management of NoSQL, Streaming, and Caching platforms (Cassandra, Aerospike, Kafka, Redis) across AWS and GCP. Build highly available, self-healing systems with automated failover and scaling, develop comprehensive observability solutions, and lead incident response for critical data platform issues. Drive automation-first practices and apply AI/ML approaches such as anomaly detection and predictive scaling to enhance reliability and reduce manual toil. Partner with engineering and platform teams to ensure resilient infrastructure supporting billions of transactions and millions of players globally.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs. Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.

Senior Software Engineer working within the Knowledge Exploitation & Decisions Systems Group to build scalable microservices and high-performance APIs for command & control, trusted AI, and advanced reasoning systems. You will take technical ownership of features within a mature mission planning solution, translating complex mathematical models from PhD scientists into production-grade software. Required: 5+ years (BS) or 1-2+ years (MS) of professional experience building maintainable APIs; strong proficiency in Java 17+, Spring Boot, and object-oriented design patterns; experience with Linux, Docker, Kubernetes, and DevSecOps practices.

As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions. You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace. Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

Join Qualcomm's Enterprise AI Engineering organization as a BizAI Tech Functional Engineer, bridging business stakeholders in Finance, Sales, and SCM with the AI engineering team. You will design and deliver AI-driven agents, natural-language analytics, and workflow automations on Qualcomm's unified BizAI platform, integrating with enterprise systems like Databricks, Oracle, Salesforce, and M365. The role requires full-stack technical expertise (Python, TypeScript, FastAPI, n8n, Kubernetes) combined with functional fluency to translate process pain points into governed, production-grade solutions that meet SOX, security, and auditability standards. You'll support adoption through enablement and hands-on guidance while defining standards for scalability and compliance across the enterprise.

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions. Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

Senior Firmware Engineer role focused on developing and optimizing low-level embedded software in C++ for flight-critical avionics and unmanned aerial systems (UAS). You will port frameworks to new RTOSes and hardware platforms, create Board Support Packages and Hardware Abstraction Layers for ARM Cortex-M architectures, develop peripheral drivers (I2C, SPI, UART, ADC, wireless), and conduct unit/integration testing including MISRA C compliance checks. You'll diagnose cross-domain issues across electromechanical, software, networking, and RF subsystems, and translate mission requirements into technical specifications and test documentation.

As a Staff Software Engineer in Data Platform Engineering, you will design, build, and operate cloud-native platform components and services, taking features from design through production. You'll lead well-scoped technical projects, collaborate with senior engineers on architecture alignment, and ensure reliability and scalability through testing and instrumentation. You'll spend most of your time hands-on building operators, controllers, automation, and platform services that other teams depend on, while mentoring junior engineers. The role requires 8+ years of software development experience (or equivalent with advanced degrees), 5+ years of hands-on Kubernetes experience, and proficiency with at least one major hyperscaler (AWS, Azure, GCP).

Design, implement, and maintain secure DevSecOps automation frameworks across on-premise and cloud infrastructure, integrating security controls into CI/CD pipelines for application and configuration deployment. Develop Infrastructure as Code using Terraform, Ansible, ARM/Bicep, PowerShell, Python, and Bash across Windows, Linux, VMware, Azure, and hybrid environments. Automate provisioning, patching, vulnerability remediation, and compliance checks aligned with FFIEC, NCUA, CIS, and NIST standards while partnering with Cybersecurity, Infrastructure, and Application Development teams. Support container/platform engineering, cloud identity governance, and promote DevSecOps and GitOps practices across technology teams.

Own the complete release and deployment strategy for Elemynt's secure AI infrastructure platform, building systems that ensure every release is versioned, reproducible, observable, and safe to operate across enterprise and scientific computing environments. Design and implement deployment automation, CI/CD pipelines, artifact management, and operational visibility (logs, metrics, alerts) that work reliably in customer-managed and restricted environments. Debug incidents, identify root causes, and systematize fixes into reusable automation. Partner with product and engineering teams to embed deployment readiness into the platform from the start.

Design and own cloud infrastructure foundations, core platform services, and observability systems that enable reliable deployment across customer environments (on-premise, cloud, or hybrid). Build production-grade Kubernetes infrastructure, internal APIs, deployment pipelines, and monitoring/alerting layers using infrastructure-as-code. Instrument service-level objectives and health signals to ensure measurable reliability and reproducible, secure deployments across all environments.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams. The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.

Senior DevOps / Platform Engineer (Level III) responsible for designing and maintaining CI/CD pipelines, automating infrastructure for predictable environments, and supporting containerized platforms in secure, regulated defense settings. The role requires 5+ years of hands-on experience with Kubernetes, container technologies (Docker, Podman, Buildah), CI/CD tools (GitLab, Jenkins, AWS CodeBuild), infrastructure-as-code (Terraform, Ansible, CloudFormation), and Linux systems. You will work directly with software and cyber engineers to solve delivery problems, build microservices pipelines, and adapt to evolving program requirements across U.S. Navy modernization initiatives.

SRC seeks a mid-level platform engineer with 5+ years of CANES experience and 5+ years in IT systems design/integration to analyze existing OpenShift cluster deployments and design solutions addressing identified gaps. The role involves creating Ansible automation to integrate OpenShift clusters with CANES network, identity, and PKI services; performing on-platform installation, configuration, and troubleshooting; and authoring technical documentation. The engineer will work autonomously to identify technical limitations, test solutions, and propose technology improvements while optionally mentoring junior team members.

SAIC seeks a Senior Software Engineer to integrate AI capabilities into expeditionary systems for the Navy, including sensor kits, unmanned systems, command & control, and TAK. The role spans hands-on development—maintaining Zenoh data mesh in Rust, building React frontends in JavaScript, integrating machine learning models, converting tactical message formats—and technical leadership with senior management. Required qualifications include 9+ years as a software engineer, data engineer, or data scientist; expert Python; intermediate Rust or Go; experience with containerization, event streaming platforms (Kafka, Kinesis, RabbitMQ, Zenoh), tactical data standardization, and data pipeline deployment. Successful candidates will collaborate with ML engineers, systems engineers, and field teams to ensure high-quality data flow and operational performance.

Staff engineer role focused on integrating autonomy software across Shield AI's Hivemind platform, spanning simulation, hardware-in-the-loop, and flight systems. Responsibilities include developing deep expertise in the autonomy stack, configuring and deploying multi-agent systems, integrating new autonomy capabilities, enabling platform bring-up on new robotic hardware, architecting integration tooling and deployment infrastructure, ensuring cross-platform compatibility, diagnosing integration defects via telemetry analysis, and optimizing CI/CD workflows. The role bridges engineering development and real-world autonomous applications, requiring systems integration expertise, robotics platform knowledge, and hands-on proficiency with sensor drivers, middleware, and deployment frameworks.

Staff Software Engineer responsible for adapting mobile control station software applications to a cloud environment, with focus on Infrastructure-as-Code, containerization, and deployment to Il-5 cloud infrastructure. Will collaborate across Software Engineering, Systems Engineering, Cloud & Application, and DevOps teams in an Agile environment, working on containerization, instrumentation, integration, security, and system testing. Requires 8-12 years of software engineering experience (depending on degree level) and hands-on expertise with cloud platforms, infrastructure components, IaC tooling, Docker/Kubernetes, software-defined networking, and scripting/coding languages.

Senior Cloud Engineer to design, deploy, and maintain scalable cloud infrastructure and services across development, testing, and production environments. Responsibilities include developing infrastructure as code (Terraform, CloudFormation), building CI/CD pipelines, managing cloud security and access controls, automating operational processes, and troubleshooting complex infrastructure issues. Requires 5+ years of cloud engineering or DevOps experience, hands-on expertise with AWS/Azure/GCP, and proficiency with Linux, scripting languages (Python, Bash, PowerShell), Docker, and Kubernetes.

SAIC seeks a Cloud DevOps Engineer to design, build, and operate mission-critical cloud infrastructure on AWS and Kubernetes/OpenShift platforms in support of Naval Operational Architecture. The role combines infrastructure-as-code (CloudFormation, YAML), container orchestration, Linux/Windows server administration, networking, scripting (Bash, Python, PowerShell), and cybersecurity hardening (STIGs, ACAS). You will work across cyber, networking, and development teams to deliver resilient, secure, and highly available cloud environments while maintaining compliance and system uptime.

BAE Systems seeks a Software Engineering Intern III for Summer 2027 to develop new code, resolve critical problems, and improve system stability within the Electronic Systems division. The intern will work alongside experienced engineers on real-world aerospace and defense projects, gaining hands-on experience with modern software architectures, frameworks, and databases. Required skills include proficiency in Java, C++, C#, Python, or JavaScript, along with knowledge of data structures and object-oriented programming. The role offers exposure to cloud platforms (AWS, Azure), containerization (Kubernetes, Docker), frontend frameworks (React, Angular), backend tools (Spring, Gradle), and various databases (SQL, NoSQL).

As an Associate Software Engineer on the Digital Product Development team, you will participate in full-stack, full-cycle product development for cloud-native applications and IoT device lifecycle management platforms. You'll design, develop, and deploy web applications and services using languages like Java, React, and JavaScript, with emphasis on PaaS/IaaS, serverless services, and container technology. Responsibilities include code reviews, CI/CD pipeline development, automated testing, and building reliable, scalable cloud-native applications following security best practices. The role requires solid technical acumen, strong problem-solving skills, and the ability to work collaboratively in a fast-paced, high-growth environment.