Jobs at Source Direct

Lead client security and compliance initiatives, including CMMC Level 2 and ISO 27001 implementations, audit readiness, control development, and regulatory monitoring. Operate within Microsoft GCC High and cloud environments, apply risk-based security practices, support incident response exercises, and provide technical leadership across diverse client programs.

Own the post-sale customer lifecycle for enterprise software customers by driving adoption, value realization, retention, and growth. Build executive relationships, develop customer success plans, coordinate cross-functional resources, resolve complex issues, communicate product value, and support renewals through metrics gathering, pricing, quoting, negotiation, and closure.

Develop and document enterprise-grade SaaS platform functionality while improving quality and performance. Responsibilities include full-stack development, functional and unit testing, defect triage, code reviews, API and process documentation, operational support in regulated environments, and collaboration within Agile and DevOps teams. The role requires expertise in C#, ASP.NET Core, T-SQL, Entity Framework Core, web technologies, software design, debugging, distributed architectures, and high-performance APIs.

Design and scale a feature flagging and A/B testing platform, including high-throughput event ingestion, warehouse-native analytics, real-time feature flag delivery, multi-database SQL support, and distributed systems infrastructure. The role involves full-stack development, architecture, performance optimization, reliability engineering, and technical product influence within a remote startup team.

Own fleet-scale infrastructure and SRE architecture for an edge platform supporting thousands of devices. Lead reliability, scalability, secure lifecycle management, observability, incident response, upgradeability, and operational standards. Serve as technical owner during high-severity incidents, drive root-cause remediation, apply AI to operations, and coordinate cross-domain initiatives spanning software, hardware, networking, security, data, and AI runtime. Mentor senior engineers and provide architectural leadership across the organization.

Own the technical aspects of enterprise airline deals from qualification through deployment and expansion. Design integration and cloud architectures, lead demos and proofs of concept, respond to RFPs and security questionnaires, review technical contracts, and ensure customer commitments align with engineering capabilities. Build reusable technical assets, support adoption, and communicate customer requirements to product and engineering teams.

Designs and owns production machine learning systems for game development and live operations. Responsibilities include querying large-scale data warehouses, exploratory analysis, statistical testing, feature engineering, experimentation, model deployment in cloud environments, and collaboration with engineering and product teams. The role also involves mentoring junior data scientists, communicating insights to technical and non-technical stakeholders, and promoting data-driven decision-making.

Build and operate production AI platform capabilities, including agentic and multi-agent systems, evaluation and monitoring frameworks, fine-tuning workflows, inference optimization, safety controls, APIs, and rollback mechanisms. Partner with data and infrastructure teams to deliver reliable, scalable AI services while balancing latency, cost, GPU utilization, and operational risk. Senior engineers also mentor teammates, review designs, and raise engineering standards.

Build and own the company’s iOS mobile application from the ground up, with Android planned next. Develop mobile UX, integrate authentication, payments, databases, APIs, and existing AI technology, and contribute across the backend when needed. Translate designs into polished production code, ship rapidly, iterate using user feedback and data, and establish mobile engineering practices. Collaborate closely with engineering, product, and design in a fast-paced, in-office startup environment.

Owns end-to-end customer deployments of AI and edge systems, including hardware, networking, sensors, data flows, integrations, and production inference. The role requires diagnosing cross-stack issues, building reusable deployment patterns, collaborating with customer and partner engineering teams, and translating field learnings into product improvements. It involves 25–50% travel and hands-on work across infrastructure, security, containerized software, and operational environments.

Build and scale a permitting platform using React, Remix, TypeScript, Prisma, PostgreSQL, and AWS. Collaborate with customers and teammates, shape product direction and architecture, ship frequently, and establish engineering practices. The role emphasizes product-minded development, user empathy, clear communication, rapid delivery, and experimentation with AI-assisted workflows. Candidates should have at least two years of professional full-stack product development experience and be based on the West Coast, preferably in the San Francisco Bay Area.

Owns operational readiness for an existing SaaS product portfolio and partner-enabled offerings. Establishes readiness frameworks, standardizes release and enablement processes, coordinates cross-functional execution, manages third-party partner alignment, and incorporates customer feedback into planning. Tracks readiness, efficiency, and partner metrics while communicating risks and dependencies to stakeholders. This remote individual contributor role requires influencing teams without direct authority and includes occasional travel.

Provides expert technical guidance to customers adopting and scaling cloud-native platforms. Responsibilities include architectural advising, platform implementation support, troubleshooting distributed systems, reviewing code, collaborating with engineering and sales teams, contributing to open-source projects, and maintaining strong customer relationships. The role requires Kubernetes experience, programming knowledge, technical communication skills, and empathy in high-pressure support situations.

Build and operate production-grade private AI platform capabilities, including agentic and multi-agent workflows, orchestration, evaluation, monitoring, fine-tuning, runtime optimization, safety controls, APIs, and rollback mechanisms. Partner with data and infrastructure teams to improve reliability, performance, and deployment quality. Senior engineers also mentor teammates, review designs, and lead major platform components.

Manage a portfolio of 20–25 technical SaaS customers across onboarding, adoption, renewals, and expansion. Build success plans, connect product usage to business outcomes, advise customers on QA and automated testing, engage technical and executive stakeholders, manage risks and escalations, and partner with Sales, Product, and Engineering. Own renewal and expansion forecasting while delivering net and gross dollar retention targets.

Build and operate core data infrastructure for edge and hybrid environments, including ingestion, OT/IoT integrations, real-time streaming, data contracts, schemas, validation, lineage, observability, telemetry, and scalable query access. The role requires production ownership, reliability practices, customer integration, and collaboration across engineering and customer-facing teams. Candidates should have 6+ years of experience with production data, streaming, or integration systems and proficiency in Python and/or Go.

Build and operate production data and streaming systems across edge, hybrid, OT, IoT, and enterprise environments. Responsibilities include developing connectors, real-time event-driven pipelines, data contracts, schemas, validation, lineage, observability, telemetry, federated query patterns, and reliable integration platforms supporting analytics and AI. The role requires strong ownership, system design, documentation, incident readiness, and collaboration with engineering and customer-facing teams.