AI-ML Engineer

VeeRteq Solutions Inc.; New York (NY); Remote; USD 140,000 - 210,000; Full time

Job summary

VeeRteq Solutions Inc. is seeking a Senior AI-ML Engineer to design, implement, test, and deploy agentic AI systems and multi-agent workflows that solve complex customer problems.

You will lead technical discussions, mentor the technical team, and own major solution areas end-to-end, leveraging AWS Bedrock, Terraform, and robust IAM patterns across AWS accounts.

Qualifications

• 5-7+ years building production-grade ML or GenAI systems; advanced Python.
• Hands-on with agentic frameworks (Strands, LangGraph, CrewAI or similar).
• Strong prompt engineering and context engineering (grounding, RAG, memory patterns).
• Cross-account IAM architecture design for multi-agent systems across AWS accounts.
• API integration experience; IaC using Terraform or CloudFormation.
• AWS Bedrock including Models and Guardrails; basic AWS services.

Responsibilities

• Design, implement, test, and deploy agentic AI systems and multi-agent workflows.
• Lead technical discussions, drive architecture decisions, and mentor the team.
• Architect and integrate agent orchestration frameworks with tool/API ecosystem.
• Own and deliver major solution areas end-to-end with minimal oversight.

Skills

years building ML/GenAI systems

Python

agentic frameworks

prompt engineering

IAM architecture

API integration

Infrastructure as Code

AWS Bedrock

Tools

Terraform

CloudFormation

Lambda

API Gateway

S3

IAM

KMS

Secrets Manager

ECR

AWS Bedrock

Job description

Role: AI-ML Engineer (Senior)

Location: US (remote)

Duration: 12 Months +

Key Responsibilities

• Design, implement, test, and deploy agentic AI systems and multi-agent workflows to solve complex customer problems
• Lead technical discussions, drive architecture decisions, and mentor the technical team
• Architect and integrate agent orchestration frameworks with tool/API ecosystem
• Own and deliver major solution areas end-to-end with minimal oversight

Must Have

• 5-7+ years building production-grade ML or GenAI systems; advanced Python
• Hands-on experience with agentic frameworks (Strands, LangGraph, CrewAI or similar)
• Strong prompt engineering and context engineering (grounding, RAG, memory patterns); MCP/A2A experience
• Cross-account IAM architecture experience - designing and implementing IAM roles, trust policies, and permission boundaries for multi-agent systems that span AWS accounts
• API integration experience (consumer/client); IaC using Terraform or CloudFormation
• AWS Bedrock (Models, Guardrails); Lambda, API Gateway, S3, IAM, KMS, Secrets Manager, ECR, Basic VPC

Should Have

• Bedrock AgentCore Services; CloudWatch, DynamoDB, EventBridge, Step Functions, ECS Fargate
• Agent evaluation experience (automated scoring, performance tracking)
• Inter-agent communication patterns (MCP, A2A) in multi-account environments - cross-account invocation, service control policies (SCPs), and resource-based policies for agent-to-agent access
• API Security (OAuth2, ApiKey, BasicAuth)
• Observability (logging, metrics, tracing); CI/CD pipeline setup
• Vector databases and retrieval patterns
• GenAI coding assistants (Kiro, Q Developer)
• Legacy technology familiarity (Java/Spring, Sybase, DB2, or COBOL) as source context for agentic modernization or integration pattern design
• Financial services or regulated-industry experience (compliance-aware delivery: trade surveillance, data controls, audit requirements)
• Large-scale portfolio delivery experience - reusable patterns or components applied across 50+ applications, including wave planning and throughput measurement