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General Summary:The Sr. Digital Delivery Specialist at EMSTEEL designs, builds and delivers advanced AI and machine-learning solutions that create measurable business value across the Group’s steel and building-materials operations. The role sits within the Digital Centre of Excellence and focuses on Generative AI, Agentic AI, Computer Vision, AI Digital Twins and productionizing models through modern MLOps practices applied to industrial use cases such as process optimization and predictive maintenance. Working end-to-end from use-case discovery and experimentation to deployment, monitoring and adoption. Essential Duties and Responsibilities:Partner with business stakeholders and SMEs to identify, qualify and prioritize high-impact AI/ML use cases aligned to EMSTEEL’s strategic objectives.Design, develop and deploy Generative AI solutions (LLM-based assistants, RAG pipelines, document intelligence, summarization and content generation) tailored to enterprise needs.Build Agentic AI systems — autonomous and multi-agent workflows that reason, plan, use tools and orchestrate tasks, including Agent-to-Agent (A2A) collaboration and protocols across enterprise applications.Deliver industrial AI use cases across the value chain — process optimization, predictive maintenance, quality prediction, energy and yield optimization, and anomaly detection for steel and building-materials operations.Develop and operationalize AI Digital Twin solutions that simulate, monitor and optimize plant assets and production processes in real time.Build Computer Vision solutions for defect detection, surface-quality inspection, safety monitoring and process automation on the shop floor.Develop, validate and optimize classical and deep-learning models for prediction, optimization, anomaly detection and process control.Implement robust MLOps practices: CI/CD for models, automated pipelines, feature stores, model registry, versioning, monitoring, drift detection and retraining.Engineer scalable data and AI pipelines on Databricks and integrate solutions across the Microsoft (Azure) stack and Dataiku.Own end-to-end AI project delivery — from proof-of-concept to production — ensuring quality, security, performance and on-time delivery.Drive AI adoption by embedding solutions in downstream applications, updating SOPs, enabling users and delivering relevant training and change management.Establish responsible-AI, governance, evaluation and guardrail practices for GenAI and agentic solutions (accuracy, safety, bias, data privacy and cost control).Communicate findings, model behavior and business impact clearly to both technical and non-technical audiences.Additional Duties and ResponsibilitiesContribute to the AI reference architecture, reusable components and internal best-practice standards.Stay current with emerging GenAI/agentic frameworks, foundation models and tooling, and pilot promising innovations.Mentor junior Sr. Digital Delivery Specialists and analysts and support a culture of experimentation and continuous learning.Knowledge, Skills and/or Abilities RequiredStrong hands-on experience in machine learning, deep learning and statistical modelling using Python (and SQL).Proven expertise in Generative AI LLMs, prompt engineering, RAG, embeddings, vector databases and fine-tuning.Experience building Agentic AI solutions and multi-agent / Agent-to-Agent (A2A) systems using frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen or similar.Experience delivering industrial AI use cases process optimization, predictive maintenance and AI digital twins.Hands-on Computer Vision experience (OpenCV, PyTorch/TensorFlow, object detection, segmentation, defect/anomaly detection).Solid MLOps capability MLflow, model deployment, containerization with Docker/Kubernetes, CI/CD, GitHub / GitHub Actions and model monitoring.Proficiency with Databricks (Spark, Delta Lake, Unity Catalog, notebooks) for large-scale data and ML workloads.Working knowledge of the Microsoft/Azure AI stack (Azure Machine Learning, Azure OpenAI, Azure AI Foundry, Fabric/Synapse) and Dataiku.Ability to translate business problems into technical solutions and communicate results effectively.Strong problem-solving, stakeholder-management and cross-functional collaboration skills.Minimum Requirements (Must Have):EducationBachelor’s / Master’s in Computer Science, Data Science, AI, Statistics, Engineering, Physics or Mathematics.Experience4+ years in data science / machine learning delivery.Demonstrated delivery of GenAI or agentic solutions to production.2+ years implementing cutting-edge AI/GenAI technologies.Exposure to manufacturing, heavy industry or steel operations.Experience with responsible-AI governance and LLMOps.Training / CertificationsCertifications in Machine Learning / AI, Databricks, Microsoft Azure AI or Dataiku.

Project descriptionExpert-level engineer designing and building LLM applications and agentic workflows on Azure: RAG pipelines, multi-agent orchestration, MCP tool integration, evaluation, guardrails and cost control. Sets the GenAI engineering standards for the account and is accountable for solution quality against agreed evaluation thresholds.ResponsibilitiesBuild LLM applications and agent workflows with LangGraph / LangChain / Semantic Kernel on Azure OpenAI (AWS Bedrock / GCP Vertex a plus).Design RAG pipelines: document ingestion, chunking strategies, embeddings, vector search (Azure AI Search, FAISS, Pinecone), hybrid retrieval and re-ranking.Integrate enterprise tools and context via Model Context Protocol (MCP) servers and function / tool calling; design multi-agent systems.Engineer, version and test prompts; run offline and online evaluations (accuracy, grounding, hallucination rate) and fine-tuning where justified.Implement responsible-AI guardrails (content filters, PII redaction, policy checks) and LLM observability (tracing, token accounting, latency).Optimise token and inference cost (model routing, caching, batching); report against cost budgets.Document prompts, evaluation results and model choices; mentor engineers adopting GenAI patterns.SkillsMust haveBachelor's degree in Computer Science, Engineering, Information Systems or a related field, or equivalent practical experience.10+ years in software or data engineering, of which 3+ in machine learning / NLP and 2+ delivering production LLM applications (RAG, agents) on Azure OpenAI or equivalent.Expert Python; LangGraph, LangChain and/or Semantic Kernel; asynchronous, event-driven application design.Azure OpenAI, Azure AI Search, Azure AI Foundry / ML, Functions, Container Apps / AKS, Key Vault, Application Insights.RAG design: chunking, embeddings, vector databases (Azure AI Search, FAISS, Pinecone), hybrid search, re-ranking.MCP server / client development, function calling, multi-agent orchestration and state management.LLM evaluation (RAGAS, promptfoo, Azure AI evaluation or equivalent), fine-tuning (LoRA / PEFT) and model selection.Guardrails (Azure AI Content Safety, NeMo Guardrails or similar), LLM observability (LangSmith, OpenTelemetry), FinOps for inference.Nice to haveAWS Bedrock or GCP Vertex AI.Semantic caching, model distillation, small-language-model deployment.Azure AI Engineer Associate (AI-102) or equivalent.Experience in financial services, sovereign wealth / investment holding or other regulated enterprise environments.Experience working with distributed teams (onsite UAE with nearshore India / offshore Poland squads).LanguagesEnglish: C1 Advanced

We are looking for an experienced AI Development Engineer to join an exciting enterprise AI transformation project with a leading consulting organization.If you have hands-on experience building GenAI applications, RAG pipelines, AI agents and enterprise AI solutions, we would love to hear from you!Key Responsibilities:Develop GenAI applications, RAG pipelines, AI agents, copilots and automation workflows.Build responsive user interfaces using React, Next.js and TypeScript.Develop APIs, data connectors and AI integrations using Python and Azure AI services.Build PoCs, MVPs and reusable AI solutions for enterprise clients.Support AI testing, performance optimization, hallucination checks and responsible AI implementation.Required Skills & Experience:5–8 years of experience in software development, AI, cloud or automation.Strong hands-on experience with Python, FastAPI, React or Next.js.Experience with Azure OpenAI, Azure AI Foundry and Azure AI Search.Strong knowledge of RAG, embeddings, vector databases, prompt engineering and AI agents.Experience with APIs, Git, CI/CD, containers and automated testing.Good communication skills and experience working in Agile teams.All applications will be treated with strict confidentiality.

Job DescriptionThe Agentic AI Developer will lead the translation of agentic research into production-grade components that enhance CRM automation and decisioning. The role requires ownership of end-to-end delivery: designing prototypes, validating behaviours against business metrics, and deploying resilient services that operate under real customer workloads. Success will be measured by increased automation coverage, demonstrable reductions in manual effort, and stable, auditable agent behaviour in production.Key ResponsibilitiesDesign and implement agentic AI features that automate CRM workflows and decision tasks.Develop reliable orchestration layers to coordinate multi-step agent actions and external integrations.Integrate multiple LLM providers and maintain model selection logic to meet latency and cost SLAs.Create evaluation suites and metrics to assess agent correctness, safety and long-term effectiveness.Build monitoring, alerting and runbooks to mitigate failures and unintended behaviours.Collaborate with product managers, platform engineers and support teams to prioritise use cases and measure business impact.Maintain development and testing infrastructure used for agent experimentation and deployment.RequirementsProven track record delivering AI or agentic prototypes into production systems.Substantial experience with Large Language Models and orchestration tooling; familiarity with major providers and fine-tuning techniques.Strong software engineering skills in Python, TypeScript or similar languages and experience building robust APIs and services.Practical experience creating evaluation frameworks, A/B tests and metrics-driven product iterations.Operational experience managing servers, CI/CD and deployment tooling for ML services.Excellent stakeholder communication with an ability to translate technical trade-offs into product decisions.

Company OverviewOpen Innovation AI is a global technology company that specializes in developing advanced solutions for managing AI workloads. Its flagship product, the Open Innovation Cluster Manager (OICM), orchestrates complex AI tasks efficiently across diverse infrastructures. The platform is hardware-agnostic, optimized for various GPUs and accelerators hardware, and facilitates seamless integration and scalability for enterprise AI applications. Open Innovation AI focuses on optimizing and simplifying AI workload management and making AI technologies accessible to organizations of all sizes. With its innovative solutions, companies can reduce operational costs, accelerate time to value, and maximize their return on investment, ensuring that their AI strategies contribute directly to enhanced business outcomesRole Overview:You will work directly with customers on their hardest problems, then design and build AI systems to solve them.Most of what you build will sit on top of the OI Platform, which provides the underlying infrastructure: model inference, agent orchestration, retrieval and the broader AI tooling layer. Your focus is not on rebuilding the foundation, but on applying it effectively. You will concentrate on the customer-specific layer: workflows, data integrations, user interfaces, and the points where the platform meets a live operation.Teams are small, autonomy is high, and you own each project from kickoff through production. A typical day may involve discussing architecture with a colleague, preparing customer data, building a web application on top of the platform, integrating with SAP or Oracle, prototyping an agent, and presenting results to executives.**You build it, you ship it, you own it**This is a strong environment for engineers who want to develop real depth. You will learn how to break down ambiguous problems, evaluate real tradeoffs, work directly with modern AI tooling, and grow within a team that will challenge you.Role Responsibilities:Embed with the client and work alongside their stakeholders to translate business problems into technical solutions.Build AI solutions on top of the OI Platform, including agent workflows, RAG pipelines, custom applications, and data products that connect the platform to the customer's enterprise systems.Own the full lifecycle: discovery, architecture, build, deployment, and iteration once real users are on the system.Transform large, complex, real-world data into formats that AI systems can use effectively.Collaborate with product engineers, deployment strategists, and the customer's team on both the solution and the surrounding strategy.Travel to client sites when the work calls for it: running workshops, debugging live systems, and building trust with the people you are delivering forRequired skills & Experience:A strong engineering background in computer science, software engineering, mathematics, physics, or data science.4+ years in backend, data, or full-stack engineering. More senior and more junior candidates are welcome to apply; please indicate where you sit.Genuine proficiency in Python or TypeScript (either is acceptable).Hands-on experience with modern AI tooling: LLMs, RAG, vector databases, agent frameworks, evaluations, and prompt orchestration.Experience working with large-scale data, cloud platforms (AWS, GCP, or Azure), and modern data tooling.The ability to hold a substantive conversation with a CTO and a non-technical executive in the same meeting.A strong sense of ownership: you make decisions, ship work, and move forward without waiting to be directed.Comfort with ambiguity, shifting priorities, and problems that have not been solved beforePreferred Experience:Experience deploying AI/ML systems in regulated or mission-critical environments.Experience working directly with enterprise customers in a delivery or consulting capacity

ABOUT THE ROLEIn this role, you will design and build next-generation applications powered by AI agents on the Microsoft Azure ecosystem. You'll own features end-to-end, from responsive front-end experiences to scalable back-end services and agent orchestration layers, building applications for, driven by, and consumed by AI agents - combining strong full stack fundamentals with cutting-edge agentic AI development.Please note that this is a hybrid role, requiring office attendance at least twice a week.RESPONSIBILITIESDesign and build full stack, production-grade applications based on AI agents and multi-agent architectures.Develop modern, responsive web UIs supporting conversational experiences, real-time streaming agent responses, and dashboards for monitoring agents.Build robust back-end services and APIs (REST, gRPC, MCP) in Python (FastAPI), enabling agent-to-agent and agent-to-system communication.Develop agentic workflows using frameworks such as Semantic Kernel, AutoGen, LangChain/LangGraph, or Azure AI Agent Service.Integrate LLMs via Azure OpenAI Service, including prompt engineering, function/tool calling, and RAG pipelines.Design chunking and indexing strategies for RAG pipelines (semantic chunking, hybrid search, re-ranking) to optimize retrieval quality.Build and maintain evaluation pipelines for LLM/agent outputs (e.g., RAGAS, promptfoo, or custom eval frameworks) to measure accuracy, relevance, and reliability.Design cloud-native solutions using Azure Functions, AKS, Container Apps, Cosmos DB, and Azure AI Search, including data models across SQL and NoSQL stores.Implement secure, observable, cost-optimized systems using Azure Monitor, Key Vault, Entra ID, and CI/CD pipelines with infrastructure-as-code.REQUIREMENTS8+ years of full stack engineering experience, with at least 3 years on the Azure stack.Strong back-end skills in Python, with a solid grasp of distributed systems and microservices.Hands-on experience building applications with LLMs and agent frameworks (Semantic Kernel, AutoGen, LangGraph, or similar).Strong front-end proficiency in modern frameworks, typed JavaScript, semantic HTML/CSS, and responsive, accessible UI design.Experience with Azure OpenAI, Azure AI Foundry, and vector databases (Azure AI Search, Cosmos DB vector search).Proven experience with RAG architectures, embeddings, chunking/indexing strategies, prompt orchestration, and tool/function calling.Hands-on experience with evaluation frameworks for LLM/agent outputs and defining quality metrics for AI systems.Experience designing end-to-end agentic solution architectures (multi-agent orchestration, tool/agent boundaries, error-handling and fallback strategies).Experience building real-time features (WebSockets, SignalR, SSE) for streaming AI/agent responses.Solid understanding of authentication/authorization (OAuth2, Entra ID) and DevOps practices (CI/CD, IaC, Docker/Kubernetes).SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.