Location
London

Hours
Full Time

Salary
Negotiable

About the Role
Salesforce is hiring Forward Deployed Engineers focused on Data 360, Salesforce's real-time data engine that unifies data from any source. As a Forward Deployed Engineer, you will be a hands-on Technical Builder who configures, builds, tests, and deploys Data 360 directly inside enterprise customer environments. You will turn approved solution designs and acceptance criteria into working implementations across ingestion, harmonization, identity, insights, activation, retrieval, security, and operational readiness.

Data 360 is the data foundation for Agentforce, grounding agents in accurate, real-time enterprise data through deep data engineering. You will work with advanced technologies including RAG, vector search, MCP, and agent-to-agent integration, going beyond typical data roles.

You will collaborate within a delivery team including architects, deployment strategists, Agentforce FDEs, account teams, and customer technical teams. Engagements may span focused proofs, production rollouts, and stabilization phases, always working with real customer data, disciplined testing, and ensuring a supportable handoff.

This is a hands-on data and software engineering role involving writing SQL, Python, and Apex; building ingestion pipelines; debugging identity resolution; and shipping working implementations from sandbox through production. This role is not purely declarative configuration or advisory.

Key Responsibilities:
- Build and configure directly in customer sandboxes and production using Data 360 configuration, SQL, Apex, Flow, Python, REST Query API, Interaction SDK, Salesforce DX, CLI, Git, Data Kits, and deployment tooling.
- Engineer data layers including ingestion, harmonization, and identity resolution across batch and streaming sources.
- Materialize data views optimized for application, analytical, and agentic workloads, balancing latency and cost.
- Collaborate with customer data and AI teams to align implementations with existing strategies.
- Create representative test data and validate outcomes across various scenarios.
- Design and maintain AI data integration layers including RAG, vector databases, search indexes, and knowledge bases.
- Implement protocols for agent communication such as MCP and agent-to-agent communication.
- Build secure, scalable data integration patterns connecting Agentforce to enterprise applications.
- Apply data governance and security expertise ensuring compliance with enterprise policies.
- Troubleshoot complex issues including ingestion failures, schema drift, identity anomalies, and API errors.
- Make informed implementation decisions documenting tradeoffs and recommendations.
- Utilize AI tooling to automate build processes and accelerate customer value.
- Collaborate closely with customer technical teams through pairing, code reviews, and configuration reviews.
- Support deployment, validation, production handoff, and early stabilization.
- Provide feedback to Product and Support teams based on reproducible platform gaps and edge cases.

Join Salesforce to be part of a company leading workforce transformation in the agentic era, where innovation and AI drive customer success and business impact.

Experience
- 5+ years in software engineering, data engineering, or technical implementation including detailed experience with production data solutions.
- Hands-on experience implementing Salesforce Data 360 (Data Cloud) or comparable enterprise data platforms covering ingestion, modeling, identity, insight, activation, and operations.
- Experience building data pipelines and integrations using technologies such as Snowflake, Databricks, BigQuery, Redshift, Kafka, cloud object storage, or enterprise MDM platforms.
- Proficient in SQL with ability to build, debug, and optimize complex queries.
- Fluent in at least one enterprise implementation language such as Apex, Java, Python, or JavaScript/TypeScript, with willingness to learn others.
- Knowledge of data modeling, APIs, integration patterns, batch and streaming processing, and data access methods.
- Experience building retrieval systems for AI applications including vector databases, search indexes, embedding pipelines, or knowledge bases.
- Implemented secure service-to-service integration patterns (OAuth, SAML, event-driven architectures) and familiarity with agent protocols like MCP.
- Skilled in implementing secure data access with rigorous testing including permissions, entitlements, consent, and user context.
- Strong troubleshooting skills using logs and query evidence to isolate product behavior from configuration errors.
- Ability to implement against documented architectures and communicate technical details to customer teams.
- Experience delivering alongside customers, partners, or internal teams in deadline-driven environments.

About You
- Excited to work directly with customer administrators, developers, data engineers, and architects.
- Detail-oriented, methodical, and proactive in problem-solving.
- Collaborative team player with excellent communication skills.

Qualifications
- Bachelor's degree in Computer Science or equivalent practical experience.
- Relevant certifications in Salesforce Agentforce, Data 360, and Salesforce Platform are highly desirable.