A- Work from
- United Kingdom
- Contract
- Full-time
- Experience
- Senior
- Posted
- 12 November 2026
- Apply by
- 11 January 2027
As a Senior Forward Deployed Engineer (FDE) at Aerospike, you will embed directly with customer engineering teams to build and ship these real-time systems. You will bridge software engineering and customer operations: writing production-ready code, integrating Aerospike with enterprise data systems and AI frameworks, and validating performance under real production workloads.
Global leaders, including Adobe, Airtel, Barclays, Criteo, DBS Bank, Experian, Grab, HDFC Bank, PayPal, Sony Interactive Entertainment, The Trade Desk, and Wayfair, rely on Aerospike for customer 360, fraud detection, real-time bidding, profile stores, recommendation engines, and other use cases.
At Aerospike, we dream big and deliver even bigger. Our mission is to unleash the power of the world’s real-time data with a database built for infinite scale, speed, and sustainability.
If you're ready to shape the future of data, join us.
About the role
As AI transitions from analysis into action, enterprises need an operational foundation that connects autonomous workflows to live data—backed by authoritative state, low-latency context, and strict runtime controls.
In this role, you will take technical requirements from problem discovery through implementation and rollout. Beyond customer delivery, you will contribute directly to Aerospike’s core capabilities by turning engagement-specific solutions into reusable libraries, reference architectures, and tooling.
Responsibilities
- Embed with Customer Teams: Work side-by-side with client engineers to translate operational challenges and specs into clean technical designs, integration plans, and verifiable delivery milestones.
- Write and Integrate Production Code: Implement scalable services and integrations across Aerospike, enterprise data systems, vector engines, and agent orchestration frameworks.
- Validate Production Readiness: Own technical validation through launch: debug distributed systems issues, profile bottlenecks, and ensure systems operate reliably under high traffic.
- Benchmark and Test: Test real-world operational characteristics—including p99 latency, throughput, cache invalidation, context freshness, failure recovery, and policy enforcement—beyond basic model benchmarks.
- Build Reusable Field Assets: Identify recurring customer requirements and feed them back into internal engineering to create reusable starter kits, SDK wrappers, test fixtures, and documentation.
- Collaborate Cross-Functionally: Partner with Product, Core Engineering, and Solutions teams to resolve platform bugs, close functional gaps, and assist client teams with deployment best practices.
Requirements
- 5–8+ years of hands-on software development experience building and deploying backend services, distributed systems, or high-throughput data platforms in production.
- Strong Coding Proficiency: Fluency in at least one modern systems or backend language—Go, Java, Python, or C/C++—with solid fundamentals in concurrency, API design, and asynchronous patterns.
- Data Modeling & Storage Foundations: Practical experience working with low-latency key-value stores, distributed databases, or streaming data platforms (e.g., Kafka, Redis, Cassandra, Aerospike).
- Applied AI & Context Pipelines: Hands-on experience building services that interface with LLMs, retrieval-augmented generation (RAG) architectures, vector databases, or agent frameworks (e.g., LangChain, LlamaIndex, Temporal).
- Enterprise Integration & Security: Experience implementing authentication/authorization (OAuth, RBAC/ABAC), data validation, and auditable logging in sensitive environments.
- Collaborative Problem-Solving: Ability to navigate ambiguous requirements, communicate technical trade-offs to customer engineers, and work independently with minimal oversight.
Helpful Experience
- Hands-on experience with the Aerospike Real-time Data Platform, Aerospike Vector Search (AVS), or Aerospike Graph.
- Experience with distributed task queues, checkpointing, or durable workflow engines (e.g., Temporal, Airflow).
- Background with containerized deployments (Docker, Kubernetes) and cloud environments (AWS, GCP, or Azure).
- Familiarity with distributed tracing tools (OpenTelemetry, Prometheus, Jaeger).
Compensation and Impact
- Evaluation Metric: Success is evaluated on working production outcomes, robust software delivery, and the creation of reusable assets—not billable hours or professional services utilization.
- Comprehensive US Benefits: Competitive base salary, equity options, 401(k) matching, comprehensive health/dental/vision coverage, and remote home office support.
Aerospike is an Equal Opportunity Employer. We are committed to an environment free from discrimination based on race, religion, gender identity, sexual orientation, age, disability, or veteran status.
To keep our recruitment pipeline as high-performance as our database, Aerospike uses AI-driven tools to streamline resume reviews, scheduling, and communication. While we love smart tech, we value human connection even more. AI helps us optimize the process, but real people make 100% of the actual hiring decisions.
About Aerospike
Aerospike is the real-time database for mission-critical use cases and workloads, including machine learning, generative, and agentic AI. Aerospike powers millions of transactions per second with millisecond latency, at a fraction of the total cost of ownership compared to other databases.
What You’ll Build
- Authoritative State Foundations: Build and deploy real-time distributed data models for agent, session, and workflow state. Support high-concurrency reads and writes while meeting explicit requirements for freshness, consistency, and failover recovery.
- Context Assembly Layers: Implement pipelines that join transactional data, streaming sources, vector search indexes, and graph relationships so agent workflows make decisions based on real-time, permission-aware context.
- Execution Guardrails: Integrate policy checks, authentication/authorization boundaries, execution governors, and human-in-the-loop review steps into real-time application paths.
- Auditing and Traceability: Build logging and tracing hooks that record context snapshots, decisions, tool execution, and state mutations to meet enterprise compliance and security standards.
- Closed-Loop Execution Flows: Connect and automate the operational loop: State → Context → Action → Mutation → Updated State, ensuring downstream results reliably inform the next cycle.
How You’ll Work with Customer & Internal Teams
Senior FDEs are the primary builders and integration engineers responsible for delivering working Operational AI implementations into production.
- Professional Services manages baseline infrastructure provisioning, platform migrations, cluster sizing, and general configuration.
- Technical Account Management (TAM) maintains the day-to-day account relationship and long-term operational health.
- Your Focus: You lead the technical integration, custom data modeling, and application code. You are not responsible for routine account administration, ticket escalation, or generic maintenance support.
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