Embedded Software Project Manager

As Lead Software Engineer – AI, Data Visualization & Platform, you will help bridge architectural vision, product innovation, advanced visualization, and day-to-day engineering execution.

You will work closely with our Lead Solutions Architect, Products Integrative Director, Technical Project Manager, and Staff and Senior Developers across front-end and back-end teams. You will contribute to both our current production platform and the next generation of our technology.

This is a hands‑on technical leadership role, with approximately 70% of your time dedicated to technical execution and 30% focused on technical leadership, mentorship, and team development.

You will bring strong software engineering experience, architectural thinking, curiosity, and a practical interest in AI and emerging technologies.

Key Responsibilities

• Mentor and support developers while fostering a culture of technical excellence, curiosity, and continuous learning.
• Drive the practical adoption of AI-assisted development tools and workflows across the engineering team.
• Establish effective practices and guidelines for using AI while maintaining strong standards for code quality, testing, security, and code review.
• Collaborate with the Lead Solutions Architect on architecture, system design, and technical direction.
• Partner with the Products Integrative Director to explore and translate new product ideas into technical solutions.
• Evaluate emerging technologies and prototype approaches that can create meaningful product or engineering advantages.
• Work closely with the Technical Project Manager to ensure technical feasibility, identify risks, and support reliable delivery.
• Participate in occasional onsite deployments and international travel when required.

2. Technical Excellence & Hands-on Development (70%)

• Write and maintain production-quality code for critical system components across the full stack.
• Evolve and progressively modernize our Angular and C#/.NET Core platform.
• Contribute to scalable architectures, distributed systems, APIs, data flows, and third-party integrations.
• Help introduce next‑generation capabilities involving cloud‑native applications, containerization, event‑driven systems, and modern deployment practices.
• Develop and integrate AI‑powered features into production software, helping move initiatives from experimentation to reliable capabilities.
• Contribute to AI applications involving LLMs, agents, RAG, embeddings, intelligent search, workflow orchestration, and related technologies.
• Help develop advanced, interactive, and real‑time data visualization experiences for complex datasets such as financial markets, elections, sports, mapping, and dashboards.
• Optimize real‑time data systems, integrations, performance, reliability, and deployment processes.
• Collaborate with Staff and Senior Developers on technical design and code reviews.

Qualifications

Essential Qualifications

• 10+ years of professional software development experience.
• Experience in a senior technical role, such as Lead, Staff, Principal, Technical Lead, or equivalent.
• Strong hands‑on experience with software development and system design.
• Experience designing scalable applications, APIs, distributed systems, or complex data flows.
• Professional experience with C#/.NET and Angular/TypeScript, or closely related technologies.
• Experience working with cloud‑based, distributed, or real‑time applications.
• Practical experience applying AI or Generative AI to software development, engineering workflows, or products.
• Ability to move between detailed technical implementation, architecture, and broader product discussions.
• Strong problem‑solving, communication, and collaboration skills.
• Ability to work effectively in a fast‑paced environment with demanding deadlines.
• A hands‑on mindset: this is not a management‑only position.

Nice-to-Have Qualifications

• AI‑assisted coding, software modernization, or developer enablement.
• LLM applications, agents, tool calling, RAG, embeddings, vector search, or workflow orchestration.
• Production AI systems, including considerations related to reliability, latency, cost, security, privacy, observability, and evaluation.
• Advanced data visualization using technologies such as D3.js, Highcharts, ECharts, Plotly, Three.js, Canvas, SVG, WebGL, or WebGPU.
• Geospatial visualization, mapping, dashboards, or other data‑intensive interactive applications.
• Real‑time data technologies such as Kafka, WebSockets, messaging systems, or event‑driven architectures.
• SQL and NoSQL databases, high‑