Forward Deployed Engineer

Technical Skills — AI in Focus

The FDE is a practitioner, not a theorist. Their technical range spans foundational software engineering to modern AI and ML. The following areas represent the core of what is expected:

AI and Generative AI. Hands-on experience with LLM integration (OpenAI, Claude, Gemini), prompt engineering, RAG architecture, AI agent design and multi-agent orchestration (LangChain, Crew AI, AutoGen), and the fundamentals of fine-tuning. The candidate keeps pace with a field that changes weekly.

Data and Analytics. SQL and NoSQL, data modeling, pipeline design (ETL/ELT), BI tooling, and the ability to work fluently with both structured and unstructured enterprise data.

Cloud and Infrastructure. Proficiency in at least one major cloud platform (Azure preferred, AWS or GCP acceptable), containerization with Docker and Kubernetes, API design and integration, and enterprise security fundamentals.

Software Engineering. Python is required. Proficiency in at least one additional language. Comfort with full-stack development when the situation calls for it.

Enterprise Systems Literacy. Familiarity with ERP, CRM, or domain-specific platforms such as SAP, Salesforce, or trading systems — not as a developer, but as someone who understands the data that lives there and how to work with it.

Role: Senior Forward Deployed Engineer

This role will be approximately 60% technical and 40% functional.

We have 4 openings and are looking to fill each of these openings with someone who has worked in each of the following business domains:

1. Finance/Accounting (1 opening)
2. Manufacturing / Plant Maintenance with MES / PLM (1 opening)
3. Food / FMCG (1 opening)
4. Agribusiness / Commodities with Salesforce (1 opening)

Job Description:

The Role

This is not a traditional engineering role. A Forward Deployed Engineer sits at the intersection of business transformation and emerging technology skills — equally at home in a boardroom conversation about supply chain strategy and a whiteboard session architecting an AI-powered decisioning system. The role demands someone who can serve simultaneously as translator, builder, and trusted advisor.

The right candidate brings 12 or more years of experience spanning both the industry or functional side and deep technical capability. This is a role for someone who thrives in ambiguity, operates with startup rigor, and measures success by business outcomes, not activity.

What You Will Do

The Forward Deployed Engineer embeds directly with business stakeholders to understand their business problem and outcomes desired before designing the solution. They lead transformative solution engagements end-to-end, from problem definition through build, deployment, and value based, measurable outcomes.

Day-to-day, this means architecting, engineering, and deploying AI-first solutions in 90 days or less: LLM-powered agents, RAG pipelines, GenAI workflows, and intelligent automation in real enterprise environments. It means translating ambiguous strategic problems into crisp technical requirements, and turning technical constraints into trade-offs that leadership can act on. It means working in sprint mode – building and delivering working prototypes in days, iterating directly with users, and ruthlessly prioritizing what moves the needle.

Critically, the FDE uses their domain background as a credibility bridge. They challenge assumptions with the authority that comes from a deep understanding of the business, and earning the trust with both C-suite and engineering leaders. What they build for one domain becomes a replicable playbook for others.

Experience, Business domain expertise and Background

We are looking for at least 12 years of combined industry and technology experience — with meaningful time spent operating inside the business, not just alongside it. Finance, Banking, Supply Chain, Manufacturing, Commodities, or a comparable domain: the candidate must have held functional roles and understand how decisions actually get made at the operational and executive level.

Domain depth. Functional expertise in at least one of Finance / Banking, Supply Chain / Logistics, Manufacturing / Operations, or Commodities / Trading — sufficient to challenge domain assumptions and earn peer-level credibility with business leads.

Transformation track record. A history of defining transformation initiatives, not merely participating in them. This means owning outcomes, navigating organizational complexity, and driving adoption through influence.

Startup and field experience. Comfort in resource-constrained, fast-moving environments where structure is earned, not inherited. The candidate has operated with limited oversight and delivered anyway.

Executive-facing fluency. Demonstrated ability to work directly with senior stakeholders — translating strategy into execution and communicating upward with clarity and confidence.

Technical Skills — AI in Focus

The FDE is a practitioner, not a theorist. Their technical range spans foundational software engineering to modern AI and ML. The following areas represent the core of what is expected:

AI and Generative AI. Hands-on experience with LLM integration (OpenAI, Claude, Gemini), prompt engineering, RAG architecture, AI agent design and multi-agent orchestration (LangChain, Crew AI, AutoGen), and the fundamentals of fine-tuning. The candidate keeps pace with a field that changes weekly.

Data and Analytics. SQL and NoSQL, data modeling, pipeline design (ETL/ELT), BI tooling, and the ability to work fluently with both structured and unstructured enterprise data.

Cloud and Infrastructure. Proficiency in at least one major cloud platform (Azure preferred, AWS or GCP acceptable), containerization with Docker and Kubernetes, API design and integration, and enterprise security fundamentals.

Software Engineering. Python is required. Proficiency in at least one additional language. Comfort with full-stack development when the situation calls for it.

Enterprise Systems Literacy. Familiarity with ERP, CRM, or domain-specific platforms such as SAP, Salesforce, or trading systems — not as a developer, but as someone who understands the data that lives there and how to work with it.

Mindset and Character

Skills can be trained. Mindset is who you are. The qualities below are not preferences — they are the defining characteristics of an FDE who will succeed in this role.

Continuous learner. Genuine curiosity that drives self-directed learning. This person reads, experiments, and stays current not out of obligation but because they are wired that way. They treat every engagement as an opportunity to learn something new.

Embraces change and ambiguity. They do not wait for a complete picture before moving. They make sound decisions with incomplete information, adjust course as they learn, and are energized rather than unsettled by uncertainty.

Relentless problem solver. Hard problems are where they do their best work. They go deep, ask uncomfortable questions, and do not stop at the surface. They are as comfortable questioning the problem definition as they are solving it.

Bilingual communicator. They can shift fluently between a rigorous technical architecture discussion and a crisp executive summary — sometimes on the same day. Their communication is precise, confident, and calibrated to the audience.

Startup rigor and ownership. They act as if their name is on the outcome. They drive, follow through, and hold the bar high even when no one is watching. They do not wait to be told what to do next.