Salesforce

4 days ago

Senior Forward Deployed Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Lead technical delivery for complex agentic AI solutions deployed inside enterprise customer environments. Partner with a Deployment Strategist to own outcomes end-to-end—from architecture decisions to production handoff—while setting engineering standards and mentoring engineers. Design and ship agent logic, tool calls, multi-agent orchestration, guardrails, and KPI dashboards. Tackle difficult integration and deployment blockers using Salesforce and AI/data platforms, and translate field insights into the Agentforce roadmap.

Location: Sydney, Auckland

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Own customer outcomes end-to-end with a Deployment Strategist, serving as the senior technical authority and ensuring high engineering standards.
•Design and ship agentic systems on the Agentforce platform, including agent logic, tool calls, multi-agent orchestration, guardrails, and enterprise integration patterns.
•Own the data lifecycle for AI applications, including model design, processing pipelines, and data readiness across Salesforce Data 360, Snowflake, Databricks, and customer platforms.
•Resolve hard technical blockers such as data integration failures, model deployment issues, orchestration breakdowns, and performance regressions.
•Mentor other engineers through code reviews and pair sessions, codifying reusable patterns and playbooks from real customer work.

Travel: Medium travel

Key Requirements

•6+ years of software engineering or technical delivery experience with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS environments.
•Degree in Computer Science or a related field.
•Expertise in at least one of Python, JavaScript/TypeScript, Java, or Apex, and working across the others.
•Integrated LLMs into production and used frameworks like LangChain or LlamaIndex, applying prompt engineering and responsible AI practices.
•Deep experience in data modeling, processing, and analytics across platforms like Salesforce Data 360, Snowflake, or Databricks.

Experience:6+ yearsEnterprise AICloudSaaSLLMsData analytics

Education:Bachelor's in Computer Science

Skills:Architectural judgmentMentorshipClear communicationGet-things-done mindsetInnovation mindset

Certifications:Salesforce AdministratorPlatform Developer IPlatform Developer IIAgentforce SpecialistSystem Architect

Tech Stack:AgentforceApexLWCFlowsSalesforce APIsPythonJavaScriptTypeScriptJavaLLMsLangChainLlamaIndexSnowflakeDatabricksSalesforce Data 360CursorClaudeVibesDevOpsCI-CD

Company Brief

Salesforce

Provides a leading cloud-based customer relationship management (CRM) platform with sales, service, marketing, analytics, and integration tools that empower businesses to manage customer relationships and digital transformation at scale.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1999

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Salesforce

4 days ago

Senior Forward Deployed Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Sydney, Auckland

Workplace: Hybrid

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Seniority: Mid level

Key Responsibilities

•Own customer outcomes end-to-end with a Deployment Strategist, serving as the senior technical authority and ensuring high engineering standards.
•Design and ship agentic systems on the Agentforce platform, including agent logic, tool calls, multi-agent orchestration, guardrails, and enterprise integration patterns.
•Own the data lifecycle for AI applications, including model design, processing pipelines, and data readiness across Salesforce Data 360, Snowflake, Databricks, and customer platforms.
•Resolve hard technical blockers such as data integration failures, model deployment issues, orchestration breakdowns, and performance regressions.
•Mentor other engineers through code reviews and pair sessions, codifying reusable patterns and playbooks from real customer work.

Travel: Medium travel

Key Requirements

•6+ years of software engineering or technical delivery experience with proven end-to-end ownership of scalable production systems in enterprise AI, cloud, or SaaS environments.
•Degree in Computer Science or a related field.
•Expertise in at least one of Python, JavaScript/TypeScript, Java, or Apex, and working across the others.
•Integrated LLMs into production and used frameworks like LangChain or LlamaIndex, applying prompt engineering and responsible AI practices.
•Deep experience in data modeling, processing, and analytics across platforms like Salesforce Data 360, Snowflake, or Databricks.

Experience:6+ yearsEnterprise AICloudSaaSLLMsData analytics

Education:Bachelor's in Computer Science

Skills:Architectural judgmentMentorshipClear communicationGet-things-done mindsetInnovation mindset

Certifications:Salesforce AdministratorPlatform Developer IPlatform Developer IIAgentforce SpecialistSystem Architect

Tech Stack:AgentforceApexLWCFlowsSalesforce APIsPythonJavaScriptTypeScriptJavaLLMsLangChainLlamaIndexSnowflakeDatabricksSalesforce Data 360CursorClaudeVibesDevOpsCI-CD

Company Brief

Salesforce

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1999

Glassdoor: 4.1

Website LinkedIn Glassdoor