Job Description

As a Senior Forward Deployed Engineer (Systems & Performance), you will lead the delivery of performance-critical, low-level systems into real customer environments. Your work powers how the Agentic AI Platform acquires, processes, and reasons over data in demanding, real-world operational contexts.

Senior FDEs are polyglot mission owners and battle-tested generalists with strong systems instincts. You will take end-to-end ownership of complex customer engagements involving high-performance data acquisition, edge execution, and latency-sensitive processing—from problem framing and success definition through to production deployment under real constraints.

You will work hands-on with customer engineers, operators, and stakeholders; independently lead Proof-of-Concepts (POCs) and deployments; and make sound architectural and technical decisions in ambiguous, high-pressure environments. Over time, proven solutions and patterns from the field will graduate into the core Agentic AI Platform, including acquisition engines for IoT and industrial systems.

This role is ideal for senior engineers who thrive in systems-level problem solving, real-world deployments, and owning outcomes in the field—while shaping the long-term evolution of the platform.

1. Customer Ownership & Engagement

• Own customer engagements end-to-end, from initial scoping to production deployment.
• Lead technical discovery to understand customer systems, workflows, constraints, and success criteria.
• Translate business and operational problems into clear technical designs and execution plans.
• Serve as the primary technical point of contact during POCs and deployments.

2. Systems & Performance Engineering

• Design and implement low-level, performance-critical components using Rust and/or C++.
• Build systems for data acquisition, ingestion, buffering, transformation, and real-time or near-real-time processing.
• Profile, benchmark, and optimise systems for latency, throughput, memory efficiency, and reliability.
• Make pragmatic engineering trade-offs to deliver robust systems under real deployment constraints.

3. Edge, IoT & Data Acquisition Workloads

• Deliver customer-specific acquisition engines for industrial devices, sensors, and edge environments.
• Work across diverse protocols, data formats, and deployment conditions.
• Ensure systems are resilient to partial failures, intermittent connectivity, and noisy or imperfect data.

4. Deployment & Operational Excellence

• Partner with Platform Engineering and DevOps teams to deploy and scale Agentic AI Platform environments.
• Lead post-deployment stabilisation, performance tuning, and reliability improvements.
• Own operational readiness, including monitoring, failure handling, and customer handover where appropriate.

5. Product & Platform Engineering

• Identify recurring customer needs and patterns suitable for inclusion in the core Agentic AI Platform.
• Contribute production-quality code, configurations, and architectural improvements to the platform.
• Mentor and support junior FDEs through design reviews, code reviews, and knowledge sharing.
• Actively contribute to internal documentation and cross-team technical learning.

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Statistics, or a related field.
• 4–8 years of professional experience in systems programming, performance-critical software, or infrastructure engineering.
• Strong proficiency in Rust and/or C++, including memory management and concurrency.
• Solid understanding of operating system fundamentals (threads, processes, memory, I/O).
• Proven experience delivering production systems under real operational constraints.
• Comfortable working directly with customers in high-ownership, ambiguous environments.

Preferred

• Experience building or deploying edge systems, IoT data pipelines, or industrial software.
• Familiarity with performance profiling and debugging tools (e.g. perf, flamegraphs, sanitizers).
• Experience exposing low-level systems through clean, well-designed APIs.
• Exposure to distributed systems concepts and common failure modes.
• Familiarity with Linux environments, containerisation (Docker), and basic CI/CD workflows.
• Strong sense of ownership, technical curiosity, and a proactive problem-solving mindset.

Skills