Hi,
I hope you're doing well !!
I’m Abhijeet Kumar Pandey, a recruiter at Avanciers, Inc., and I wanted to
reach out with a potentially exciting opportunity that might align well
with your background.
We're currently hiring a Agentic AI Lead / Architect role
with one of our long-standing enterprise clients, based in Columbus OH
(Onsite). This position offering the chance to work on impactful projects with
a highly collaborative team.
Job Title: Agentic AI Lead /
Architect
Location: Columbus OH (Onsite)
Job Type: Contract
Based on the latest guidance to hire a single resource who can cover
both Architect and Tech Lead responsibilities, here is
a combined JD that merges the required skills and responsibilities
from both roles.
Request you to please review the same.
Key Responsibilities
Architecture Ownership
- Own the end‑to‑end
architecture for the AI‑agent, DSL, and SFMC automation
ecosystem.
- Design agentic AI
systems, backend microservices, APIs, and SFMC integrations
(REST/SOAP).
- Define DSL schemas
(JSON/YAML) for AI‑generated workflows, ensuring extensibility,
safety, and deterministic execution.
- Establish guardrails,
validation, simulation, and compliance frameworks for AI‑generated
journeys and campaigns.
- Create and maintain system
blueprints, including data flow diagrams, integration contracts, and
deployment architecture.
Technical Leadership
- Act as the hands‑on
technical lead, guiding AI/ML engineers, DSL engineers, backend
developers, and SFMC specialists.
- Lead POCs,
prototypes, and architectural spikes to validate design decisions
and technology choices.
- Drive coding
standards, design patterns, and best practices across engineering
teams.
- Conduct architectural
reviews, code reviews, and design walkthroughs.
- Unblock teams, make
technical decisions, and ensure alignment with architectural vision.
AI/ML & Agentic Systems
- Partner with AI/ML teams
on:
- Agent frameworks (Agent
SDK, LangChain, LangGraph, CrewAI, Semantic Kernel)
- RAG pipelines,
embeddings, and vectorization
- LLM fine‑tuning,
evaluation, and safety mechanisms
- Define prompting
strategies, context engineering, and model‑interaction patterns.
Backend, Cloud & Integration Architecture
- Architect cloud‑native,
highly available systems on AWS using IaC (Terraform).
- Oversee backend
microservices, orchestration layers, and execution pipelines.
- Ensure robust
integration with SFMC components:
- Journey Builder
- Email Studio
- Data Extensions
- Personalization logic
- REST/SOAP APIs
- Ensure observability,
monitoring, logging, and reliability across all services.
Security, Governance & Compliance
- Ensure compliance with security,
privacy, and governance requirements for AI‑generated marketing
workflows.
- Define architectural
controls for safe execution, auditability, and data protection.
- Lead performance
optimization, scalability planning, and risk mitigation.
Cross‑Functional Collaboration
- Work closely with
business, product, CRM, and marketing operations teams to translate
requirements into scalable technical solutions.
- Communicate
architectural decisions clearly to both technical and non‑technical
stakeholders.
Required Skills & Experience
- 10+ years of software
engineering experience with at least 3+ years in a Tech Lead
or Architect role.
- Strong background in AI/ML
systems, including:
- LLMs
- Agentic architectures
- Prompt engineering
- RAG pipelines
- Experience designing complex
distributed systems and workflow automation platforms.
- Deep understanding of DSL
design, interpreters, ASTs, and compiler concepts.
- Strong proficiency in Python,
TypeScript, or Java.
- Experience with cloud‑native
architectures (AWS/Azure/GCP), containers, and microservices.
- Proven ability to lead
engineering teams, conduct design reviews, and drive technical
decisions.
- Excellent communication
and stakeholder management skills.
Preferred Qualifications
- Experience building AI‑driven
workflow automation or autonomous agent systems.
- Familiarity with AMPscript and
SSJS.
- Background in marketing
automation, CRM systems, or customer lifecycle design.
- Experience with security,
compliance, and governance for AI systems.
- Prior experience in fixed‑bid
or outcome‑based delivery environments.
- Experience with event‑driven
architectures and messaging systems.