Senior Director, Forward Deployed Engineer — Operational AI

Aerospike

5d•Remote

About The Position

As Senior Director, Forward Deployed Engineer at Aerospike, you will work directly with Global 2000 engineering teams to build operational AI systems that connect agents to current enterprise reality through authoritative state, relevant context, and controls for safe action. You will own technical solutions from discovery and architecture through implementation, production validation, and iteration, combining software engineering with an understanding of customer operations. Reporting to the CTO/CPO, you will connect customer challenges with product and engineering development, delivering production outcomes and creating reusable capabilities, reference architectures, and evidence to shape Aerospike’s Operational AI direction. The role involves engineering real-time business, agent, session, and workflow state; assembling timely, permission-aware context from enterprise data, vector search, and graph relationships; and building policy checks, access boundaries, execution limits, approval gates, and human intervention paths. You will translate security and governance requirements into enforceable controls and auditable records, and connect state, context, decisions, actions, consequences, and updated state in a continuous operating loop. As a team leader, you will set direction and priorities for the FDE team, hire and develop engineers, allocate capacity across engagements, and maintain hands-on technical involvement through coding, reviews, and debugging. You will collaborate with Product, Engineering, Field Engineering, Professional Services, and Technical Account Management while keeping the FDE team focused on engineering Operational AI solutions and making field learning reusable. The role is remote, with travel as needed.

Requirements

Strong track record building and delivering production software, distributed systems, or enterprise data platforms.
Strong coding skills in at least one of Java, Go, Python, or C/C++, with practical experience in APIs, data modeling, and high-throughput or low-latency systems.
Hands-on experience delivering AI applications or agent workflows, including state management, retrieval, context assembly, and evaluation.
Experience implementing authorization, policy enforcement, auditability, and sensitive-data controls in enterprise environments.
Sound judgment about concurrency, consistency, resilience, security, and operational tradeoffs.
Ability to lead with limited direction, work effectively with customers, and take ambiguous problems from discovery to reliable production.
Demonstrated experience managing engineers while remaining technically hands-on, including hiring, coaching, performance feedback, and developing technical leaders.
Strong delegation, prioritization, and stakeholder-management skills, including balancing direct contribution with team leadership across multiple engagements.

Nice To Haves

Experience with Aerospike database, vector search, graph, or cloud capabilities.
Experience with multi-agent coordination, durable execution, checkpointing, or human-in-the-loop workflows.
Experience with cloud and hybrid deployments, streaming architectures, containers, and infrastructure automation.

Responsibilities

Embed with customer engineers and domain experts to turn ambiguous operational problems into architectures, engineering milestones, and measurable acceptance criteria.
Design, code, and integrate production solutions across Aerospike, enterprise data systems, AI frameworks, and agent orchestration layers.
Own the technical integrity of Operational AI solutions through production, validating behavior, resolving systems issues, and iterating with users against real workloads.
Test latency, throughput, context freshness, concurrent state updates, failure recovery, authorization, and guardrail behavior.
Work with Product, Engineering, and Field Engineering to close platform gaps and turn field learning into reusable code, tools, reference implementations, and product improvements.
Lead technical reviews, explain tradeoffs to engineers and executives, mentor delivery partners, and document how solutions can be operated and extended.
Set direction for the FDE team by translating Operational AI strategy into engineering priorities and measurable outcomes.
Hire, coach, and develop FDEs through expectations, feedback, performance management, and career development.
Set priorities and allocate team capacity across customer engagements, balancing strategic value, delivery commitments, and workload.
Stay technically hands-on through coding, design and code reviews, and debugging while delegating ownership and avoiding bottlenecks.
Build a high-trust engineering culture with quality standards, accountability, knowledge sharing, and continuous learning.
Collaborate with Professional Services and Technical Account Management while keeping FDE focused on Operational AI solution engineering and reusable engineering outcomes.