Top Tech Jobs & Startup Jobs

Leads complex technical initiatives from planning through implementation and transition to operations. Responsibilities include SAFe Agile ceremonies, PI planning, backlog and dependency management, integrated project scheduling, risk and issue resolution, stakeholder and vendor coordination, executive reporting, testing, migration, cutover, stabilization, and compliance oversight. The role requires close collaboration across engineering, architecture, security, infrastructure, and operations teams.

Develop algorithms and analytical systems to interpret structured and unstructured data, apply statistical and scientific methods, and deliver data-driven insights for clients across public and private sectors. Collaborate with clients and teams in fast-paced environments, using Python and data science techniques to solve complex problems, including fraud detection, cancer research, and national intelligence challenges.

Designs, implements, and optimizes secure Oracle Database solutions for enterprise and mission workloads. Responsibilities include logical and physical data modeling, multi-model and geospatial data management, AI database integrations, migration strategy, data quality validation, performance tuning, backup and recovery, security, troubleshooting, and operational support. Collaborates with application, AI, data engineering, cloud, security, and customer teams. Requires 8+ years of experience, a bachelor’s degree, and active TS/SCI clearance with polygraph willingness.

Designs, deploys, secures, and operates OCI cloud security solutions and integrates audit, logging, monitoring, and telemetry with enterprise SIEM platforms. Develops secure log-collection architectures, validates data integrity and coverage, troubleshoots ingestion and mapping issues, and creates architecture diagrams, test plans, dashboards, runbooks, and stakeholder communications. Supports secure cloud onboarding, authorization, and ongoing operations in mission-focused environments.

Designs, builds, deploys, and maintains scalable cloud-native data platforms, pipelines, data lakes, warehouses, and analytics solutions. Supports cloud migration, data science, AI/ML, and business intelligence initiatives while processing structured and unstructured data. Collaborates with analysts, developers, engineers, and data consumers in agile teams, provides technical guidance, and evaluates cloud analytics technologies and architectures.

Build modern full-stack web applications, dynamic user interfaces, RESTful APIs, interactive dashboards, charts, maps, and 3D visualizations. Connect data with databases, models, and algorithms while communicating technical concepts to nontechnical audiences. Collaborate with software engineers, data scientists, and modelers, use modern web development practices, and lead application development across varied client projects. Candidates must hold a STEM bachelor’s degree and be able to obtain a Secret clearance.

Leads enterprise data pipeline and database architecture across Oracle AI Database 26ai and OCI. Designs multimodal relational, spatial, JSON, and graph solutions; manages Oracle migrations, replication, recovery, data quality, lineage, and monitoring. Guides engineers, leads technical reviews, resolves complex data issues, and develops models, migration plans, runbooks, documentation, and stakeholder communications. Requires extensive database or data engineering experience and an active TS/SCI clearance.

Build and deploy reliable AI agents that automate client workflows and integrate with enterprise systems. Responsibilities include mapping processes, designing automation roadmaps, developing evaluation frameworks and regression tests, monitoring agent performance, instrumenting audit trails, scaling systems to production, and leading workforce adoption and change management. The role also codifies reusable patterns across engagements and requires customer-facing collaboration, production AI experience, Python or TypeScript development, Secret clearance, and up to 10% travel.

Designs, builds, and maintains secure AI-enabled software solutions for mission delivery and workflow automation. Responsibilities include developing and deploying LLM, RAG, and agentic applications; building APIs and integrating AI components; using AWS compute, storage, and data pipelines; and applying modern software engineering practices. The role also involves collaborating with stakeholders, explaining AI/ML concepts, working independently, and mentoring team members.

Analyze structured and unstructured datasets using Python, R, and SQL; perform data cleansing, statistics, visualization, and machine learning; develop dashboards and lightweight applications; integrate data systems; guide algorithm development; and advise clients on data-driven decisions, data strategy, governance, and infrastructure.