Role: Forward Deployed Engineer (Senior or Principal)
Location: Remote (requires up to 25% travel)
Duration: Contract or Permanent
Top Must-Haves:
- Senior or Principal level
- Palantir certification
- Palantir Echo
- Deep full-stack proficiency: Python
- Proven track record in building and deploying AI/ML applications in production at enterprise scale
- 4+ years in customer facing or field roles
- Data Engineering Skills
Position Overview
We are seeking a Senior or Principal Forward Deployed Engineer to work directly with enterprise customers to design, build, and deploy advanced AI-driven solutions. This role requires a blend of hands-on software engineering expertise, data engineering, solution architecture, and client engagement.
The ideal candidate will partner closely with business and technical stakeholders to understand complex challenges, develop scalable AI applications, and drive successful production deployments. This individual will act as a trusted technical advisor while maintaining end-to-end ownership of solution delivery.
This position is ideal for engineers who enjoy solving complex business problems, working directly with customers, and delivering measurable business outcomes through modern AI and data technologies.
Work Environment
- 100% remote work arrangement
- Up to 25% travel for customer and stakeholder engagements
Responsibilities
- Partner with customers to understand business objectives, assess existing data ecosystems, and design AI-powered solutions.
- Lead end-to-end solution delivery from requirements gathering and architecture through deployment and optimization.
- Build and deploy generative AI, intelligent automation, and advanced analytics solutions that deliver measurable business value.
- Develop proof-of-concepts and prototypes to validate technical feasibility and business outcomes.
- Design and implement scalable enterprise AI applications that integrate with existing systems and data platforms.
- Build and maintain data pipelines supporting structured and unstructured data sources.
- Implement retrieval-based AI solutions, semantic search capabilities, intelligent agents, and workflow automation frameworks.
- Develop production-grade applications utilizing modern backend, frontend, cloud, and container technologies.
- Establish monitoring, observability, governance, and performance management practices for AI solutions.
- Collaborate with business development and customer success teams to identify additional solution opportunities.
- Provide technical feedback to product and engineering teams based on customer needs and deployment experiences.
- Create reusable frameworks, accelerators, and best practices that improve delivery efficiency across engagements.
- Mentor engineers and customer teams on AI, software engineering, and data architecture best practices.
Required Qualifications
- Professional certification on an enterprise AI, analytics, or data platform.
- 6+ years of experience in software engineering, data engineering, machine learning, artificial intelligence, or related technical disciplines.
- 4+ years working directly with customers in consulting, field engineering, solutions engineering, or similar client-facing roles.
- Demonstrated success deploying production-grade AI/ML solutions within enterprise environments.
- Strong Python development experience.
- Experience with modern web application development technologies and APIs.
- Hands-on experience with:
- Large Language Models (LLMs)
- Prompt engineering
- Retrieval-augmented generation (RAG)
- Vector databases
- Data pipelines
- Agentic AI frameworks
- AI application development
- Experience designing and deploying cloud-native solutions.
- Strong DevOps and infrastructure automation experience including containerization, orchestration, and CI/CD.
- Experience integrating enterprise applications, data warehouses, data lakes, and operational systems.
- Ability to translate complex business requirements into scalable technical solutions.
- Excellent communication and presentation skills with both technical and executive stakeholders.
Preferred Qualifications
- Experience with enterprise AI platforms, data integration platforms, or large-scale digital transformation initiatives.
- Knowledge of model fine-tuning, evaluation frameworks, model optimization, and AI governance practices.
- Experience building intelligent agent ecosystems and autonomous workflow solutions.
- Familiarity with GPU-enabled infrastructure and high-performance computing environments.
- Previous experience in consulting, solution delivery, customer engineering, or forward deployed engineering roles.
- Domain expertise in one or more of the following:
- Energy
- Manufacturing
- Supply Chain
- Financial Services
- Healthcare
- Defense
- Experience with semantic modeling, knowledge graphs, metadata management, and ontology-driven architectures.
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