Agentic AI Engineer, Senior

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real content. From posting: There's an introductory paragraph about team, then "Work you'll do" which is responsibilities. Then "The team" description maybe about role? Could be "About the role". Then qualifications: Required and Preferred sections. Also wage range (Pay). Benefits: mention discretionary annual incentive program. Schedule: travel up to 50% maybe schedule? Not exactly schedule but travel requirement. Could be considered schedule? Might be better to include Travel under Requirements? But we have to follow headings: we can include Schedule if travel % is given. It says "Ability to travel up to 50% on average". That's schedule/travel. We'll include Schedule section. Benefits: mention discretionary annual incentive program. Also maybe other benefits not listed. We'll include Benefits with that. Pay: wage range $122,000 to $240,500. Qualifications: Required and Preferred bullet lists. Skills: maybe we can extract from required: experience delivering AI/ML solutions, Python, agentic AI, etc. Could be under Skills. But we already have Qualifications covering required and preferred. The instruction: Use sections like Qualifications, Skills. We need to decide what to put where. Could put required experience under Qualifications, and technical skills under Skills. But we must not invent content. Let's parse: Required: - 4+ years experience delivering AI/ML solutions, with at least 1 year focused on Generative AI, Agentic AI or multi-agent systems - 2+ years hands-on experience building AI/ML solutions using Python - 1+ years direct experience developing agentic AI systems, including agent orchestration, tool integration, autonomous decision-making workflows (list of tech) - 1+ years experience leading project workstreams/engagements, translating business problems into AI solutions, delivering measurable outcomes - Bachelor's or Master's degree in CS, Engineering, Data Science, AI, or related field - Ability to travel up to 50% on average Preferred: - Prior consulting experience in client-facing delivery roles - Experience creating critical collaterals for client workshops and customer interactive sessions - Presentation skills with high degree of comfort with both large and small audiences - Experience building multi-agent systems (task delegation, coordination, autonomous decision-making) - Certifications: list - Experience with LLM prompt engineering, fine-tuning, RAG - Experience with MLOps/AIOps, CI/CD pipelines, cloud-native app development - Experience with API design, microservices architecture, event-driven systems We could put Required under Qualifications, Preferred under Skills? Or Qualifications includes both required and preferred. But we have separate Skills heading; we could put technical skills under Skills (like Python, agentic AI, Azure/AWS/GCP services, LLM prompt engineering, MLOps, API design, etc). However we must not invent content; we can extract those from required and preferred. Better: Use Qualifications for education and experience requirements (degree, years experience, travel). Use Skills for technical skills list (Python, agentic AI, Azure/AWS/GCP, LLM prompt engineering, MLOps, API design, microservices, event-driven). Use Responsibilities for work you'll do. Use About the role for introductory paragraph and team description. Use Pay for wage range. Use Benefits for discretionary annual incentive program. Use Schedule for travel up to 50% (though travel already in Qualifications; but we could move travel to Schedule). Let's decide: Qualifications: degree, years experience, leading project workstreams. Schedule: travel up to 50%. Skills: technical skills list. Benefits: discretionary annual incentive program. Pay: wage range. Now we need to ensure we don't repeat content. We'll include each piece once. Let's craft sections:

About the role

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals reimagining and re-engineering operations and processes that are critical to businesses. Your contributions can help clients improve financial performance, accelerate new digital ventures, and fuel growth through innovation. AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements. The team Our AI & Data practice offers comprehensive solutions for designing, developing, and operating advanced Data and AI platforms, products, insights, and services. We help clients innovate, enhance, and manage their data, AI, and analytics capabilities, ensuring they can grow and scale effectively.

But note we repeated "The team" paragraph; we can combine. Better: About the role includes first paragraph and team description. Now Responsibilities:

Responsibilities

• Managing day-to-day interactions with executive clients, stakeholders, and sponsors
• Managing and delivering components of client engagements focused on identifying, designing, and implementing both technology and creative business solutions for large companies
• Managing small teams to identify business requirements, functional design, process design (including scenario design, flow mapping), prototyping, testing, training, defining support procedures
• Creation and development of project scope and schedule. Plan and assign resources to associated tasks and deliverables
• Monitoring progress of the project, identify, and quantify variances, perform required corrective actions
• Managing changes to project scope, project schedule, and project costs to keep the project plan accurate, updated, as defined in the change management plan
• Identifying high-level risks, assumptions, and constraints. Implement approved actions and workarounds to minimize the impact of risks on the project
• Developing and maintaining communication with key project stakeholders and decision makers

Now Qualifications:

Qualifications

• 4+ years of experience delivering AI/ML solutions, with at least 1 year focused on Generative AI, Agentic AI or multi-agent systems
• 2+ years of hands-on experience building AI/ML solutions using Python
• 1+ years of direct experience developing agentic AI systems, including agent orchestration, tool integration, and autonomous decision-making workflows (e.g., LangChain; Semantic Kernel, AutoGen, Strands; CrewAI. LangGraph)
• 1+ years experience leading project workstreams/engagements, translating business problems into AI solutions, and delivering measurable outcomes
• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI, or related field

Now Skills:

Skills

• Experience with Azure: AI Foundry (design, deployment, orchestration of AI/agentic applications); OpenAI Service (LLM integration for reasoning, planning, and tool use); Cognitive Search & Vector DBs (retrieval, memory, context for agents); Cognitive Services (vision, speech, and language APIs for agent capabilities); Entra ID & Key Vault (identity, security, compliance for AI workloads)
• Experience with AWS: Amazon Bedrock (foundation models, model evaluation, and agent orchestration); Knowledge bases (retrieval, metadata filtering, re‑ranking), Guardrails, Prompt Flows, and RAG pipelines for enterprise‑grade agentic solutions; Lambda, ECR and EC2 based deployment; Amazon Q Business & Q Developer (enterprise AI assistant and code generation capabilities); Cognito (identity, security, compliance for AI workloads); IAM, Secrets Manager, and KMS
• Experience with GCP: Vertex AI (e.g., Model Garden, Agent Builder, custom training); Gemini API and Google AI Studio; BigQuery (for data processing and analytics); Cloud Run, Cloud Functions, and GKE (for agent deployment)
• Experience with LLM prompt engineering, fine‑tuning, and RAG (Retrieval Augmented Generation) architecture
• Experience with MLOps / AIOps (monitoring, governance, lifecycle), CI/CD pipelines, and cloud‑native application development
• Experience with API design, microservices architecture, and event‑driven systems
• Presentation skills with a high degree of comfort with both large and small audiences
• Experience creating critical collaterals for client workshops and customer interactive sessions
• Prior consulting experience in client‑facing delivery roles
• Certifications: Azure AI Engineer Associate, Azure Solutions Architect Expert; AWS Certified Machine Learning - Specialty, AWS Certified Solutions Architect - Professional; Professional Machine Learning Engineer, Professional Cloud Architect

Now Benefits:

Benefits

• Eligibility to participate in a discretionary annual incentive program, subject to program rules, with awards based on individual and organizational performance

Pay:

Pay

The wage range for this role is $122,000 to $240,500.

Schedule:

Schedule

Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve.

We should not include repeated info like travel also in Qualifications; we moved it to Schedule. Ensure we didn't duplicate any content elsewhere. We removed travel from Qualifications. Good. Check that we preserved all substantive info: Intro paragraph, team description, responsibilities list, qualifications (degree, experience years, leading workstreams), skills (Azure, AWS, GCP specifics, LLM prompt engineering, MLOps, API design, presentation, collaterals, consulting, certifications), benefits (discretionary annual incentive), pay range, schedule travel. Also note we omitted "Limited immigration sponsorship may be available" - that's substantive; should we include? It's a detail about immigration sponsorship. It's not covered in any section; we could add to Qualifications or Benefits? It's not a benefit exactly but could be under Qualifications as a note. However we must not invent sections; we could add a short paragraph under Qualifications or maybe under About the role? Better to add a small note in Qualifications as a bullet: "Limited immigration sponsorship may be available". That is substantive. Let's add. Also note "Recruiting for this role ends on 9/30/2026." That's a date; could be included maybe in About the role or a separate metadata but instructions say drop minor metadata into a short

or drop it. It's minor; we can drop it or include a short p. Probably drop it as per instruction: "do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

or drop it." So we can drop it. Also note "At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case." That's commentary about pay; we could include in Pay section as a sentence. It's substantive about compensation. Let's add to Pay paragraph. Also note "The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled." Also pay detail. Include. Thus Pay section will have multiple sentences. Now Benefits: also maybe mention "You may also be eligible to participate in a discretionary annual incentive program..." we already have. Now check for any other substantive info: "Ability to travel up to 50% on average, based on the work you do and the clients and industries/sectors you serve." Already in Schedule. Now