Software Gigs

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.

As a Cybersecurity Engineer and Risk Analyst, you will develop and implement security solutions to protect military infrastructure, performing vulnerability and compliance assessments using industry-standard tools like eMASS and ACAS. You'll troubleshoot complex security challenges, assess network and system threats, implement infrastructure controls, and communicate security risks to both technical and non-technical audiences. The role requires 3+ years of experience leading Risk Management Framework (RMF) activities for DoD projects, vulnerability scanning, and security control implementation. You'll work closely with Navy missions to identify cyber risks, recommend solutions, and provide hands-on support using your knowledge of cybersecurity policy, networks, system infrastructure, and risk management.

Lyntris seeks a Cyber Security Engineer II to provide Risk Management Framework (RMF) Assessment and Authorization (A&A) support for Navy software solutions. The role involves designing, implementing, and monitoring cybersecurity and information assurance policies for mission-critical systems; developing system IA documentation (categorization forms, security plans, assessment plans, continuous monitoring plans, risk assessments); and guiding the software development team through security scan review, evaluation, and remediation. The engineer will work with system owners and stakeholders to manage cybersecurity requirements and continuously improve cyber posture. Requires 2–3 years of Department of Navy accreditation experience and working knowledge of NIST standards, RMF, and eMASS.

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.

Software Developer I/II at G2 Software Systems will perform full-cycle software engineering—planning, requirements analysis, design, development, integration, testing, and debugging—on large-scale mission-critical defense systems for DoD air defense, counter-drone, secure communications, and C4ISR operations. The role requires 3+ years of Java and JavaScript full-stack web development experience, proficiency with Agile processes, and hands-on work in automated build environments (Git, GitLab, Bitbucket, Jira, Confluence). Candidates must be U.S. citizens capable of obtaining and maintaining a DoD security clearance. The company emphasizes custom software, AI/ML, cybersecurity, and MBSE across defense engineering solutions.

As a Staff Graphics Software Engineer, you will architect, design, implement, and optimize GPU hardware, drivers, features, and tools for next-generation gaming, XR, and AI experiences. You will write complex code in C++, C, Perl, and Python across simulation, emulation, and on-device environments, develop comprehensive pre- and post-silicon tests, and collaborate with cross-functional teams and external stakeholders. The role requires 4+ years of relevant software/hardware engineering experience (or equivalent with advanced degree) and deep graphics and GPU expertise. You will work independently with minimal supervision while providing guidance to team members and influencing key organizational decisions.

Senior back-end engineer to own and re-architect the payment-terminal platform powering restaurant kiosks, currently spanning 40+ integrations across card-present terminals, processors, and cash automation. You will design a modular, pluggable SDK enabling internal and external developers to build integrations against a stable contract, implement new integrations from wire-level protocols (TLV, BMP, APDU, BCD/LLVAR) up through high-level APIs, and establish platform-wide patterns for payment correctness (idempotency, transaction recovery, reconciliation). Role requires 6+ years back-end engineering with strong Java, Spring, OOP, and distributed-systems design; hands-on work with serial (RS-232/USB-serial via jssc) and USB (usb4java) transports, REST/SOAP/webhook integrations, and PCI-DSS compliance patterns.

Senior Network Engineer supporting mission-critical defense network environments at NIWC Pacific. Responsibilities include engineering, integration, testing, and maintenance of complex Combined Test Bed (CTB) network infrastructure, with emphasis on security, STIG compliance, and multi-cloud connectivity. Required skills span enterprise routing/switching, firewall management, cloud networking across AWS and Azure, and network security technologies including Zero-Trust architectures. Must hold or be able to obtain Active Secret clearance and possess DoD 8570 IAT Level II and networking certifications.

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.

Senior embedded software engineer role developing mission-critical firmware for Amazon's Leo satellite constellation. Responsibilities include architecting ASIC firmware, RF communication subsystems, secure boot operations, real-time embedded software, and hardware interfaces using protocols like I2C, SPI, UART, and Ethernet. The role requires security-by-design principles, threat modeling, secure coding practices, and collaboration with hardware architects and systems engineers to bring custom silicon from concept through secure bring-up and production integration.

Design and build software to automate RF hardware test systems for satellite components before flight, including test infrastructure, CI/CD automation, and production-scale testing orchestration. Write Python on Linux test racks to measure satellite modem, amplifier, and RF component performance against pass/fail thresholds, translating hardware engineer requirements into reliable automated test logic. Support manufacturing validation, on-orbit failure analysis, and enable factory operators to run environmental stress testing at scale. Own software quality, release processes, and work with SCPI-controlled test instruments, thermal chambers, and telemetry dashboards that drive ship/no-ship decisions.

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).

This Quality Assurance Engineer role supports medical device product development and sustaining engineering teams by developing and implementing quality test procedures, test equipment protocols, and sampling plans. The engineer will conduct product investigations, corrective/preventive actions, regulatory submissions support, and statistical analysis of production data—all in compliance with industry standards (ISO 14971), GMP, and regulatory requirements. The role requires 4+ years in medical device/pharmaceutical quality engineering or equivalent advanced degree with 2+ years of relevant experience, with expertise in test method validation, equipment qualification (IQ/OQ/PQ), risk management documentation, and analytical equipment validation.

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.

The Database Engineer will maintain, monitor, and optimize large-scale production MySQL database environments in distributed, mission-critical settings. Responsibilities include performance tuning, query and index optimization, database migrations and upgrades, capacity planning, and 24x7 on-call support. The role requires designing reliable database architectures, automating operational tasks, and collaborating with development teams on database design guidance. Candidates must have strong fundamentals in distributed database topologies, Linux administration, scripting proficiency (Go/Python/Shell), and experience with cloud platforms such as Azure.

Senior Python Backend Engineer building and maintaining Python-based APIs and services in an AWS environment. The role focuses on developing Kafka-based data pipelines, managing data movement across systems, and ensuring reliability and performance of containerized services. You'll need strong production Python experience, familiarity with streaming or message-based systems, and comfort working with AWS and Docker.

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.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers. Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

As Principal Software Engineer for AI & Data Platform, you will architect the data foundation for scientific and engineering R&D platforms, designing scalable data processing patterns, ML training pipelines, and intelligent workflow interfaces. You will own end-to-end responsibilities including data modeling for multi-use analytics and ML, building production training and fine-tuning pipelines, model evaluation and benchmarking, and setting engineering standards for the team. The role requires 10+ years shipping production software, expert-level Python, deep experience with large-scale data systems (object storage, analytical processing, training formats), hands-on ML pipeline development, and the ability to set technical direction in early-stage environments while implementing it yourself.

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments. The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.

The Senior Systems Engineer will design, develop, and support communications and encryption devices, providing technical expertise in cryptographic technologies and deployment strategies. Responsibilities include advising on cryptographic equipment deployment, analyzing emerging threats, conducting technical analysis of cryptographic products for acquisition decisions, liaising with vendors on device lifecycle, and supporting leadership with briefings and fielding decisions. The role requires 5–15 years of cybersecurity, systems engineering, or network security experience, along with strong analytical, problem-solving, and written communication skills. A bachelor's degree in Systems Engineering, Computer Science, or related field is required.

Staff Software Engineer leading the design, architecture, and operations of PlayStation's Real-Time Analytics Platform (RTAP), a large-scale distributed data system handling high-throughput, low-latency analytics and stream processing. The role involves architecting and evolving streaming and analytics platforms using Apache Flink, Spark, ClickHouse, and Druid; integrating batch and streaming workloads via lakehouse architectures; and embedding AI capabilities to automate engineering workflows and improve platform reliability. You will own critical platform capabilities end-to-end from design through production operations, mentor engineers, establish technical standards, and influence cross-functional technical strategy across PlayStation's data infrastructure.