What are the responsibilities and job description for the AI-ML Engineer position at VeeRteq Solutions Inc.?
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