The Role
Owns end-to-end delivery of AI-powered automation, intelligent agents, copilots, and LLM workflows. Engages stakeholders, gathers requirements, designs architectures, evaluates feasibility and ROI, develops Python and Azure-based solutions, and manages testing, deployment, monitoring, and support. The role uses Azure OpenAI, LangChain, LangGraph, RAG, embeddings, APIs, microservices, and cloud data platforms while leading demos, UAT, delivery timelines, and continuous innovation.
Summary Generated by Built In
Deployed EngineerRole Overview
The Forward Deployed Engineer (FDE) operates as an end-to-end owner of intelligent automation and AI-driven initiatives. This is a highly autonomous role requiring a blend of technical expertise, functional understanding, and stakeholder management.
The FDE works directly with business teams to design and deliver scalable solutions leveraging AI/ML, Large Language Models (LLMs), LangGraph-based orchestration, Python, and Azure cloud platforms—without reliance on separate BA, architect, or developer roles.
Key Responsibilities1. Business Engagement & Requirement Gathering- Engage directly with business stakeholders to capture and refine requirements.
- Identify and assess automation and AI opportunities (e.g., GenAI, workflow automation, copilots).
- Perform feasibility analysis for implementing AI/ML or LLM-based solutions.
- Build strong relationships and act as a trusted technical advisor to business teams.
- Represent the engineering team in stakeholder discussions and strategy sessions.
- Develop Process Design Documents (PDDs) and solution architecture designs.
- Create detailed AI/ML use cases, including LLM-powered workflows and agentic systems (LangGraph-based).
- Translate business needs into scalable architectures using:
- Azure AI Services / Azure OpenAI
- LangChain / LangGraph workflows
- Python-based microservices
- Define data flows, APIs, and integration strategies across enterprise systems.
- Estimate implementation effort, infrastructure costs, and licensing requirements.
- Evaluate ROI of automation and GenAI use cases.
- Recommend optimal architecture considering cost, scalability, and performance.
- Support budgeting decisions with data-driven insights.
- Own complete Software Development Lifecycle (SDLC):
- Design → Development → Testing → Deployment → Support
- Develop solutions using:
- Python (core development, APIs, data processing)
- LLMs (Azure OpenAI, prompt engineering, embeddings, RAG)
- LangGraph / LangChain (agent orchestration, multi-step workflows)
- Build intelligent agents, copilots, and automation pipelines.
- Deliver demos and iterative updates to stakeholders.
- Set up and manage cloud infrastructure in Microsoft Azure, including:
- Azure OpenAI / Cognitive Services
- Azure Functions / App Services
- Azure Data Factory / Synapse
- Storage & databases (SQL, Cosmos DB, Data Lake)
- Implement CI/CD pipelines, monitoring, and logging.
- Collaborate with platform teams for enterprise-grade deployments.
- Identify and address gaps in tools, frameworks, and environments.
- Lead regular updates, sprint demos, and solution walkthroughs.
- Manage User Acceptance Testing (UAT) cycles and feedback loops.
- Ensure timely delivery aligned with business expectations.
- Take full ownership of delivery timelines and quality.
- Stay current with evolving technologies:
- Generative AI, Copilot ecosystems, LLMs
- LangGraph / Agent frameworks
- Azure AI advancements
- Identify opportunities to enhance processes through automation and AI.
- Proactively introduce innovative solutions and best practices.
- Programming: Python (mandatory), APIs, data processing
- AI/ML:ML fundamentals (training, evaluation, model lifecycle)
- NLP and Generative AI concepts
- LLMs & GenAI:Azure OpenAI / OpenAI APIs
- Prompt engineering, RAG, embeddings
- Fine-tuning & evaluation approaches
- LangChain / LangGraph – agent orchestration and workflow automation
- Vector databases (e.g., FAISS, Azure AI Search)
- REST APIs, FastAPI
- Azure OpenAI, Cognitive Services
- Azure Data Factory / Synapse Analytics
- Azure Functions / App Services
- Data storage (Blob, Data Lake, SQL)
- DevOps, CI/CD pipelines
- Strong blend of technical, functional, and business acumen
- Proven ability to own end-to-end solution delivery independently
- Hands-on experience with LLMs, AI/ML, and cloud-native development
- Excellent communication and stakeholder management skills
- Experience building intelligent automation or copilot-like solutions
- Self-driven problem solver with a proactive mindset
- Ability to multitask across multiple initiatives
- Balance competing priorities while maintaining delivery quality
- Adapt quickly in dynamic, fast-paced environments
- High accountability and ownership mindset
This role combines responsibilities typically distributed across Business Analyst, Solution Architect, and Developer roles, making it ideal for a highly skilled, adaptable engineer capable of driving AI-powered transformation initiatives end-to-end.
Skills Required
- Python development experience, including APIs and data processing
- Knowledge of machine learning fundamentals, including training, evaluation, and model lifecycle
- Knowledge of NLP and generative AI concepts
- Experience with Azure OpenAI or OpenAI APIs
- Experience with prompt engineering, retrieval augmented generation, embeddings, fine-tuning, and evaluation
- Experience with LangChain and LangGraph for agent orchestration and workflow automation
- Experience with vector databases such as FAISS or Azure AI Search
- Experience with REST APIs and FastAPI
- Experience with Microsoft Azure cloud services, including Azure Functions, App Services, Data Factory, Synapse, storage, and databases
- Experience with DevOps, CI/CD pipelines, monitoring, and logging
- Ability to own end-to-end solution delivery independently
- Strong stakeholder communication, functional understanding, and business acumen
- Experience building intelligent automation or copilot-like solutions
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The Company
What We Do
Anblicks is a Cloud Data Analytics Company based out of Dallas, TX, with offices in USA, India, and Australia. Since 2004, Anblicks has been helping customers by bringing value to their data and implementing modern data architecture and advanced analytics solutions in the cloud.
