Software Gigs

Own end-to-end demand forecasting and capacity planning for AI systems, compute, storage, GPU, and emulation across a global engineering organization spanning tens of thousands of servers and hundreds of petabytes of storage. Translate silicon product roadmaps and tapeout schedules into multi-year demand plans, size and justify capital purchases into the hundreds of millions of dollars, and present capacity positions to engineering and finance leadership. Build and maintain forecasting models, decision rules, and utilization analytics; apply AI and automation to move beyond manual spreadsheet work. Lead and mentor a team of analysts, raising their craft and setting analytical direction.

Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go. Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.

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.

This role involves independently designing, developing, and debugging real-time embedded software, RTOS environments, and microcontroller firmware for wireless chipsets supporting 3G, 4G, 5G, and AI technologies. The engineer will work on driver development, integration, testing, and validation of communication protocols and platforms, while also contributing to data collection frameworks, machine learning modeling, and embedded software algorithm improvements. Responsibilities include on-target development, tool and process optimization, customer support, technical documentation, and active participation in design reviews. The position requires a Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field.

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.

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.

OWT Global seeks a Cybersecurity Analyst to serve as technical authority for ServiceNow platform security, ensuring compliance with federal cybersecurity protocols including NIST SP 800-53 and DoD RMF. Responsibilities include mapping ServiceNow roles and access controls to compliance frameworks, developing and maintaining System Security Plans (SSP) and POA&Ms, supporting vulnerability management and security assessments, and providing advisory support to government personnel on cybersecurity matters. The role requires five years of practical cybersecurity experience, a Bachelor's degree in Cybersecurity or related field, and relevant certifications (CISSP or Security+ preferred), with strong understanding of ServiceNow architecture and DoD RMF processes.

Architect responsible for creating detailed plans and drawings using AutoCAD and Revit to outline project design, conducting site evaluations to ensure quality and safety compliance, and overseeing the construction process from conception through completion. The role requires strong organizational and creative skills, knowledge of engineering and materials science, and ability to collaborate with multiple teams on goals, schedules, and budgets. Requires a Bachelor's degree in architecture and 3+ years of construction and architecture experience.

As an information security risk specialist, you will work with DoD acquisition programs to identify cyber risks, assess threat landscapes, and develop mitigation strategies. You will conduct risk and vulnerability assessments across networks, systems, and applications, translate security concepts for stakeholders, and manage RMF (Risk Management Framework) and A&A (Assessment and Authorization) activities. You need 4+ years of IT systems experience with DoD/government agencies, 3+ years leading Navy RMF projects, and expertise in security policy implementation, compliance assessment, and vulnerability mitigation. A Secret clearance and DoD 8140 Certification are required.

The Maximo Business Analyst & Reporting Analyst supports and optimizes IBM Maximo solutions by analyzing business requirements, developing enterprise reports and dashboards, and driving user adoption through training. The role requires designing, developing, and maintaining reporting solutions using BIRT, Cognos, Power BI, and MAS Reporting; supporting asset management, maintenance, inventory, and procurement functions; and providing functional support and troubleshooting. Key responsibilities include gathering stakeholder requirements, creating operational and executive reporting solutions, leading Maximo 2.0 training initiatives, and collaborating on system enhancements and testing activities.

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.

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.

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.

The Accounting Systems & Data Integration Analyst supports Axos Bank's Accounting & Finance initiatives, with primary focus on Jack Henry SilverLake, Enterprise Workflow (EWF), and Loan IQ platforms. The role designs, develops, and maintains integrations between banking systems and Finance applications, manages transaction-to-GL mapping, performs data validation and reconciliation, and ensures accounting data integrity across lending, deposit, treasury, and operations. Responsibilities include requirements gathering, interface development, testing, production support, SOX/audit compliance coordination, and leveraging AI tools (Copilot, Claude) to accelerate requirements analysis, testing, and automation. The position requires 10+ years of experience in system integrations and data interfaces within banking or financial services, with strong expertise in Jack Henry platforms, Azure DevOps, ServiceNow, SQL, APIs, and file-based integrations.

Staff Software Engineer leading design and evolution of PlayStation's Real-Time Analytics Platform (RTAP), a large-scale distributed data system handling high-throughput, low-latency analytics and stream processing. Responsibilities include architecting stream processing pipelines, optimizing data services using Apache Flink, Spark, ClickHouse, and Druid, integrating batch and streaming workloads with lakehouse architectures, and building AI-powered capabilities for platform automation. The role requires deep expertise in distributed systems, real-time analytics, and mentoring engineering teams while establishing technical standards and best practices across the organization.

The Data Architect is a hands-on technical leader responsible for designing and modernizing enterprise data architecture across on-premises and cloud platforms. The role defines scalable data models, integration patterns, and architectural standards for the Data Lake, Data Warehouse, ODS, and cloud platforms while ensuring security, resilience, and high performance. Working closely with engineering, analytics, and business teams, the architect provides technical guidance on modern data systems, governance frameworks, and ETL/ELT pipelines. The position combines strategic vision with practical experience optimizing structured, semi-structured, and unstructured workloads across SQL, NoSQL, and cloud-native systems.

As a Cybersecurity Engineer and Risk Analyst, you will develop and implement security solutions to protect military infrastructure, performing risk and vulnerability assessments across networks, systems, and applications. You will leverage tools like ACAS, STIGs, and eMASS to assess security threats, implement infrastructure controls, and prepare Risk Management Framework (RMF) artifacts and Security Assessment Plans (SAP) for DoD customers. You'll troubleshoot complex cybersecurity challenges, analyze big data security events to identify advanced threats, and communicate technical findings to both technical and non-technical audiences. The role requires 3+ years of IT experience with government/DoD agencies, hands-on RMF and A&A leadership, and an active TS/SCI clearance.

Ignite Digital seeks an AI Engineer to own the end-to-end machine learning lifecycle—from data preparation and model training through production deployment and monitoring. You will integrate AI models into frontend and backend systems, optimize performance for latency and cost, and collaborate with technical leads and customers to deliver Data and AI solutions. The role requires strong Python and cloud platform expertise (AWS, Azure, or GCP), software engineering fundamentals, and the ability to communicate technical opportunities and limitations across varying levels of technical experience.

The Senior Automated Information System Analyst (SAISA) will provide IT systems support, troubleshooting, and technical training for Naval Forces Logistics systems (R-Supply, OMMS-NG, NALCOMIS) across U.S. Navy ships and shore commands. Responsibilities include NTCSS System Administrator duties, life cycle management for hardware/software, operator training, and Navy/Marine Corps Intranet (NMCI) support. The role requires extensive Linux command knowledge, experience troubleshooting Force Level NTCSS systems, and CompTIA Security+ certification with ongoing continuing education enrollment.

Staff-level engineer designing and operating large-scale distributed data platforms powering real-time analytics across PlayStation. You will lead the architecture and evolution of the Real-Time Analytics Platform (RTAP), own critical capabilities end-to-end from design through production operations, and mentor engineers. Key responsibilities include building and optimizing distributed services using Apache Flink, Spark Structured Streaming, ClickHouse, and Apache Druid; integrating batch and streaming workloads with lakehouse architectures; and establishing technical standards for distributed systems, stream processing, and data modeling.