Forward Deployment Engineer

🔥 0 minutes ago

🇮🇳 India – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

⛑ DevOps & Site Reliability Engineer (SRE)

👻 Ghost score 18%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Xenon Seven

WebsiteLinkedInAll Job Openings

11 - 50 employees

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Xenon Seven is a company that specializes in providing AI and data solutions across various industries, including healthcare, financial services, consumer retail, high-tech, automotive, and energy utilities. With expertise in generative AI, decision support systems, predictive analytics, computer vision, robotics, and mechatronics, they support businesses in AI preparedness, exploration, transformation, and scalability. Xenon Seven works with a network of AI technologists and experts from over 20 institutions, focusing on solving complex problems and ensuring secure and seamless AI transitions for businesses. Their services aim to optimize AI infrastructure and performance while maintaining strict security standards.

📋 Description

• Own the full lifecycle of AI solutions for Finance business units, from discovery with CFO stakeholders through production deployment, user adoption, and ROI measurement • Rapidly prototype vertical applications using Streamlit, Databricks Apps, FastAPI/Flask, or lightweight React interfaces within 1–2 weeks to gather real user feedback • Handle last-mile execution, including edge cases, data quirks, business rule exceptions, and user training • Build production-grade vertical AI tools leveraging Snowflake Cortex or Databricks Genie • Construct robust RAG pipelines with advanced chunking, vector databases, retrieval evaluation, grounding, and citation • Implement LLM orchestration frameworks and rigorous prompt engineering with hallucination and accuracy evaluation • Deploy applications in regulated enterprise environments while adhering to RBAC, data residency, audit, and SOX/GxP compliance constraints • Connect solutions to governed datasets, semantic models, and enterprise platforms such as SAP, Workday, Coupa, and ERP systems via secure REST APIs • Instrument deployed applications with usage metrics, telemetry, and business outcome tracking • Work directly with senior Finance leadership to translate ambiguous operational friction into technical roadmaps • Extract reusable code components, prompt templates, evaluation harnesses, and retrieval patterns into shared enterprise assets

🎯 Requirements

• 5+ years of hands-on software development and full-stack AI application deployment • Strong bias for action; comfortable shipping rough prototypes in Week 1 over polished spec documents in Week 4 • Proven ability to navigate vague business problems without predefined specifications • Outstanding ability to interface directly with senior business leaders without requiring intermediary Business Analysts • Proficiency in Python, FastAPI/Flask, SQL, and UI frameworks (Streamlit, Databricks Apps, React) • Direct hands-on experience with Snowflake Cortex OR Databricks Genie • Production experience with LangChain, LangGraph, LlamaIndex, vector search engines, and prompt evaluation harnesses • Deep working knowledge of cloud platforms (Azure preferred, AWS/GCP acceptable), modern Git workflows, CI/CD, and basic MLOps awareness (observability, versioning via LangSmith, Datadog, etc.) • Solid foundational understanding of Finance business processes (FP&A, order-to-cash, procure-to-pay, record-to-report, close cycles) and financial metrics (OPEX, EBITDA, gross margin, working capital) • Prior FDE, Solutions Engineer, or Field Engineer experience at high-growth AI/Data companies is a nice-to-have • Industry background in Life Sciences, Pharma, Healthcare, or CPG enterprise Finance is a nice-to-have • Experience with enterprise Finance software (SAP S/4HANA, Veeva, Workday Adaptive, Oracle Financials) is a nice-to-have • Certifications such as Snowflake Cortex, Databricks Certified, or Azure AI Engineer Associate (AI-102) are nice-to-haves