AI Pre-Sales Consultant

Job summary

You will independently design, code, and deploy autonomous AI agents and scalable cloud infrastructure using AWS services. Additionally, you will lead technical interviews, define coding standards, and translate complex business challenges into effective AI solutions for clients.

Job details

Role Summary We are looking for a hands-on AI Architect who can code, architect, and deploy. You must be able to take a concept from a whiteboard to a working Proof of Concept independently. This role combines deep AWS Cloud Architecture expertise with modern Agentic AI patterns to build autonomous systems that solve real business problems. You will work directly with clients across retail, financial services, healthcare, and manufacturing, translating their business challenges into working AI solutions. You will also play a key role in growing the team by technically vetting and onboarding future engineers. Core Responsibilities Hands-On Agentic AI Development You will build PoCs independently without relying on a dev team for the initial build. This means designing and coding AI Agents using AWS Bedrock and frameworks like LangChain or LangGraph, implementing reasoning, planning, and memory modules. You will configure LLMs to interact with external APIs, databases, and enterprise software to execute real-world tasks. Our clients expect working demonstrations, not slide decks. AWS Cloud Architecture (PaaS Focus) You will design scalable infrastructure using AWS PaaS services including Lambda, Fargate, API Gateway, EventBridge, and Step Functions. You will select and optimize Foundation Models via Amazon Bedrock or SageMaker based on cost, latency, and performance requirements. All architectures must meet strict security, compliance, and cost-optimization standards. Client Delivery & Solution Design You will participate in AI Discovery engagements to identify high-value opportunities within client organizations. You will translate business requirements into technical architectures that align with our outcome-driven methodology. You will work alongside our AI Strategy and Implementation teams to deliver end-to-end solutions. Team Building & Technical Leadership You will lead technical interviewing, selection, and onboarding for new hires within the AI workstream. You will define technical standards and coding guidelines for our growing AI/ML team. You will contribute to knowledge transfer initiatives, building client capabilities rather than dependencies. Multi-Cloud & Integration You will integrate AI services into existing enterprise workflows and data pipelines. You will maintain operational knowledge of Azure and GCP to support client-specific multi-cloud requirements. What You Will Work On Solutions across several domains. Here are examples of the types of projects you would contribute to: Building multi-agent systems that reduce manual decision-making by 30% and improve response times by 40%. Implementing AI-driven quality monitoring for manufacturing clients that reduces batch rejections by 25%. Developing hyper-personalization engines for retail clients that increase digital conversion rates by 20-27%. Creating data pipelines and AI infrastructure that enable new AI initiatives while reducing data preparation time by 60%. Requirements Must-Have Qualifications AWS Certification: Must hold a valid AWS Certified Solutions Architect (Associate or Professional). Hands-On Coding: Strong proficiency in Python. You must be comfortable writing production-grade code, not just managing configurations or reviewing pull requests. Cloud Background: Strong foundation in traditional Cloud Architecture including networking, IAM, and serverless patterns. We expect you to have built cloud infrastructure before moving into AI. AI Stack: Proven experience with Amazon Bedrock, SageMaker, and Vector Databases such as Pinecone or OpenSearch. Agentic Experience: Demonstrated ability to build Agents that utilize tools and function calling. We are not looking for people who have only built simple chatbots. Consulting Mindset: Ability to communicate technical concepts to business stakeholders and translate business problems into technical solutions. Nice-to-Have Qualifications Data Background: High-level understanding of Data Warehouses (Snowflake, Redshift) and Data Lakes to understand data lineage and retrieval strategies. This helps when working with our Data Foundation services. DevOps: Experience with CI/CD pipelines and Infrastructure as Code using Terraform or CDK. RAG Implementation: Experience building production RAG systems with enterprise document collections. MLOps: Familiarity with MLflow, Kubeflow, or Weights & Biases for model lifecycle management.

What you’ll do

You will independently design, code, and deploy autonomous AI agents and scalable cloud infrastructure using AWS services. Additionally, you will lead technical interviews, define coding standards, and translate complex business challenges into effective AI solutions for clients.

Requirements

Candidates must hold an AWS Certified Solutions Architect certification and possess strong proficiency in Python and cloud infrastructure. Proven experience in building agentic AI systems and a consulting mindset are essential for this role.

Listed skills

• Amazon Web Services · Preferred
• Python · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Python
• AWS
• Agentic AI
• LangChain
• LangGraph
• Amazon Bedrock
• SageMaker
• Cloud Architecture
• Vector Databases
• Pinecone
• OpenSearch
• Serverless
• API Gateway
• Lambda
• Consulting
• Solution Design
• Scalability Design
• Data Lakes
• PineCone
• AWS SageMaker
• Langgraph
• Business Problems
• Pipelines
• Vector Database
• AWS Cloud Development Kit (CDK)
• MLOps (Machine Learning Operations)
• CI/CD
• Multi-Cloud
• Pull/Merge Requests
• MLflow
• Workflow Management
• Quality Monitoring
• Snowflake (Data Warehouse)
• Data Lineage
• Data Preprocessing
• Technical Leadership
• Kubeflow
• Serverless Computing
• AWS Bedrock
• AWS Certified Solutions Architect Associate
• Infrastructure as Code (IaC)
• Knowledge Transfer
• Planning
• AI Agents
• Application Programming Interface (API)
• Multi-Agent Systems
• Artificial Intelligence
• Amazon Web Services
• Autonomous System
• Microsoft Azure

Job areas

• Technology
• Software
• Consulting
• Data & Analytics
• Engineering
• Pre-Sales Consultant
• Sales Consultant
• Commercial Sales Representatives
• Sales Representatives, Wholesale and Manufacturing, Technical and Scientific Products