Forward Deployed Engineer, AI & Analytics

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Virtasant

WebsiteLinkedInAll Job Openings

51 - 200 employees

💼 Consulting

🏢 Enterprise

🤝 B2B

Consulting • Enterprise • B2B

Virtasant is a cloud services and optimization company that helps businesses migrate to, manage, and build on public cloud platforms. They combine a proprietary automation platform with managed services and FinOps expertise to reduce cloud costs (claiming average savings of over 50%), support Cloud FinOps programs, and deliver outcome-based engagements rather than hourly or seat-based billing. Virtasant also provides enterprise AI guidance and partners with major cloud providers (AWS, Google Cloud, Azure) to deliver migration, optimization, and 24/7 managed operations.

📋 Description

• Take a Palantir Foundry proof of concept to production, including data pipelines, ontology, application layer, governance, and observability • Work with business and product teams to run discovery and turn policies and operating procedures into working code and agent logic • Define an adoption or delivery metric with the client’s business leader, own it, and report against it • Train client engineers while building so capability remains with the client • Shape the roadmap from proof of concept to a production-grade product the client can sell • Embed with the client, own an outcome, and ship • Collaborate with client product and business teams and train their internal engineers • Participate in forward-deployed AI pods accountable for measurable business results

🎯 Requirements

• 6+ years in software, data, or ML engineering with senior-level ownership of production systems • Hands-on Palantir Foundry experience, including Pipeline Builder, Ontology, and Workshop; AIP is a strong plus • Alternatively, deep experience with a comparable platform such as Databricks or Snowflake, with evidence of fast platform ramp • Production Python and SQL • TypeScript or Java is a plus • Experience building with LLMs and agents, including retrieval, tool use, evaluation, and moving beyond the demo stage • Consulting, solutions engineering, or client-embedded delivery experience • Clear written and spoken English; comfortable presenting to executives • Healthcare, staffing and workforce, or other regulated-industry domain experience is a nice-to-have • Track record of capability transfer through training, pairing, or engagement playbooks is a nice-to-have • Prior FDE, solutions architect, or solutions engineer role at a platform vendor or AI-native company is a nice-to-have

🏖️ Benefits

• Contract engagement through the Gigster network • Full-time dedication expected • Initial term aligned to the production build, with extension likely as the pod model expands across business units • Compensation is competitive and set by experience and location