Role Description
East Rutherford, NJ, United States (On-site) Contract (4 months 12 days) Published 7 days ago technical documentation performance optimization troubleshooting skills Generative AI devops rest apis microsoft azure cloud SAP Integration * We are seeking a highly motivated and hands-on Forward Deployed Engineer (FDE) to join our AI & Innovation team. This individual will operate at the intersection of business, AI research, and engineering, helping transform business problems into production-ready AI solutions. * Initially, the role will focus heavily on researching emerging AI technologies, evaluating platforms and frameworks, conducting technical feasibility assessments, and building Proof of Concepts (POCs). As AI opportunities are identified, the FDE will lead the development, integration, and deployment of AI use cases, working closely with Business Analysts, AI Architects, Data Scientists, and business stakeholders. * The ideal candidate combines software engineering expertise with strong problem-solving skills and a passion for rapidly prototyping and deploying AI-powered solutions.
Key Responsibilities:
AI Research & Innovation
- Research emerging AI, Generative AI, Agentic AI, automation, and machine learning technologies.
- Evaluate AI platforms, frameworks, models, and tools for enterprise adoption.
- Conduct technical feasibility assessments for proposed AI use cases.
- Benchmark AI solutions and recommend optimal architectures.
- Stay current with advancements in LLMs, AI Agents, RAG architectures, Copilot technologies, and automation platforms.
Proof of Concept (POC) Development:
- Design, build, and demonstrate rapid prototypes for AI use cases.
- Develop POCs that validate business value and technical feasibility.
- Create MVPs to support executive and stakeholder decision-making.
- Identify risks, limitations, scalability considerations, and implementation requirements.
- Present technical findings and recommendations to business and technology leadership.
AI Solution Development:
- Develop production-ready AI applications and services.
- Design API integrations between AI platforms and enterprise systems.
- Build AI-powered workflows, copilots, virtual assistants, and automation solutions.
- Develop Retrieval-Augmented Generation (RAG) solutions leveraging enterprise knowledge sources.
- Create scalable and reusable AI solution components.
Business & Stakeholder Collaboration:
- Partner with Business Analysts to understand business requirements and use cases.
- Collaborate directly with business stakeholders to refine AI opportunities.
- Translate business problems into technical solution designs.
- Participate in discovery workshops and innovation sessions.
- Provide technical guidance on AI capabilities, limitations, and implementation approaches.
Solution Architecture & Integration:
- Develop solution architectures for AI applications.
- Integrate AI solutions with enterprise platforms such as SAP, ServiceNow, Microsoft 365, Azure, databases, and internal applications.
- Design secure and scalable deployment architectures.
- Ensure compliance with enterprise governance, security, and responsible AI standards.
- Support cloud and hybrid deployment models.
Deployment & Operationalization:
- Support pilot deployments and production rollouts.
- Monitor AI solution performance and optimize results.
- Improve solution reliability, scalability, and maintainability.
- Troubleshoot technical issues and support continuous enhancement activities.
- Create technical documentation and implementation guides.
The pay range that the employer in good faith reasonably expects to pay for this position is $48.54/hour - $75.85/hour. Our benefits include medical, dental, vision and retirement benefits. Applications will be accepted on an ongoing basis.
Tundra Technical Solutions is among North America’s leading providers of Staffing and Consulting Services. Our success and our clients’ success are built on a foundation of service excellence. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Unincorporated LA County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: client provided property, including hardware (both of which may include data) entrusted to you from theft, loss or damage; return all portable client computer hardware in your possession (including the data contained therein) upon completion of the assignment, and; maintain the confidentiality of client proprietary, confidential, or non-public information. In addition, job duties require access to secure and protected client information technology systems and related data security obligations.
About Forward Deployed Engineering
Forward Deployed Engineers are embedded directly with customers to build custom solutions, integrate products into existing infrastructure, and bridge the gap between product engineering and customer success. The role combines deep technical skills with the ability to operate in client environments and translate business requirements into working software.
Originally pioneered by Palantir, the FDE model has spread across AI, enterprise SaaS, and cloud infrastructure companies. FDEs write production code, architect integrations, train customer teams, and feed product insights back to the core engineering organization. At companies like OpenAI, Salesforce, and Databricks, FDE teams are treated as elite engineering units that can ship custom solutions in days rather than quarters.
Typical FDE stack: Python, TypeScript, SQL, REST/GraphQL APIs, cloud platforms (AWS/GCP/Azure), and increasingly LLM APIs and AI orchestration frameworks. Strong communication and the ability to context-switch between technical and business conversations are as important as coding ability.
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