Senior AI Engineer, AI Services

AHEAD is seeking a Senior AI Engineer, AI Services to help design, build, and deploy enterprise-grade AI solutions for our clients.

This is a hands-on technical consulting role for someone who can translate ambiguous business and technical needs into practical, scalable, and secure AI solutions. You will work alongside client technology and business stakeholders, AHEAD architects, and delivery teams to understand requirements, shape solution designs, develop and integrate AI capabilities, and help move initiatives from prototype to production and measurable business value.

The ideal candidate brings strong software engineering fundamentals, applied AI and machine learning fluency, and the ability to make sound technical decisions in complex enterprise environments. You should be comfortable contributing to architecture discussions, evaluating trade-offs, developing proof-of-concept solutions, supporting production implementations, and communicating technical concepts clearly to both technical and non-technical audiences.

Success in this role requires credibility with engineers, data scientists, architects, platform teams, security stakeholders, and business leaders. You will be expected to take ownership of assigned technical workstreams, collaborate effectively across teams, proactively identify risks and dependencies, and contribute to high-quality client outcomes. You will also help share knowledge, establish repeatable delivery practices, and mentor less-experienced team members.

This role is well suited for candidates with backgrounds in applied AI consulting, machine learning engineering, AI solution architecture, technical product development, data science engineering, or advanced analytics engineering environments. Candidates should be energized by solving real-world client problems and turning emerging AI capabilities into reliable, maintainable solutions that create business impact.

Key Responsibilities

• Solution Development & Deployment
• Build and deploy multi-agent systems using frameworks such as LangChain, LangGraph, Autogen, CrewAI, and LlamaIndex.
• Develop custom agents for document processing, workflow automation, SDLC acceleration, data analysis, and business process orchestration.
• Integrate LLMs, SLMs, embeddings, and retrieval pipelines (Pinecone, Elasticsearch, Snowflake Cortex, pgvector)
• Create and operate LLM/ML endpoints, agent memory/state stores, and event-driven triggers.
• Implement reusable components that become part of AHEAD’s agent library and client solution accelerators
• Enterprise Integration & Workflow Automation
• Build real-time and batch workflows using Python, Kafka, EventBridge, Airflow, Snowflake, S3, n8n, AWS Batch, and similar tools.
• Connect agents to enterprise systems (SharePoint, Salesforce, ServiceNow, Jira, Oracle, databases, APIs).
• Implement RAG, tool-calling, function calling, and structured output pipelines for production-ready agentic tasks.
• Ensure robust data transformations, validation, and versioning for downstream agent workflows.
• Quality, Observability & Reliability
• Implement monitoring, metrics, and guardrails for multi-agent systems (timeouts, retries, constraints, circuit breakers).
• Build automated testing for agent behaviors, prompts, ETL/batch jobs, and model outputs.
• Participate in incident reviews, debugging multi-agent flows, and ensuring predictable performance.
• Client Collaboration & Delivery Excellence
• Work closely with client stakeholders to understand use cases, pain points, and success criteria.
• Translate business needs into technical agent designs and execution roadmaps.
• Participate in agile ceremonies, demos, and working sessions with client teams.
• Contribute to proposals, SOWs, architecture diagrams, and client documentation when needed.
• Security, Governance & Compliance
• Apply enterprise standards for data security, access control, auditing, model governance, and safe AI usage.
• Embed monitoring, lineage, PII handling, and policy constraints into agentic flows.
• Mentorship & Internal Development
• Coach junior engineers on agent design patterns, RAG, orchestration, and clean engineering practices.
• Contribute to internal best practices, reference architectures, and reusable components.
• Support onboarding of new engineers and help scale AHEAD's agentic engineering community.

Qualifications

• Required
• Strong Python engineering background, including async patterns, APIs, and event-driven design.
• Hands-on experience with multi-agent frameworks (LangGraph, Autogen, CrewAI, LangChain, etc.).
• Demonstrated ability to build production ETL, orchestration, or workflow automation pipelines (Kafka, EventBridge, Airflow, Celery, n8n, AWS services).
• Experience with vector DBs and retrieval pipelines (Pinecone, pgvector, Elasticsearch, LlamaIndex).
• Familiarity with MLOps, observability, CI/CD, containerization, and model deployment patterns.
• Strong documentation habits and comfort working in fast-paced agile environments.
• Experience integrating with enterprise systems or APIs in production.
• Preferred
• Experience with Snowflake Cortex, Databricks Mosaic, NVIDIA NIMs, or similar AI platform components.
• Experience operating agentic systems at scale, including safety constraints and system-level debugging.
• Experience in consulting, client-facing engineering, or co-development models.
• Success Metrics & Environment
• Delivery of reliable, scalable agentic solutions that measurably improve client outcomes.
• High client satisfaction, repeat demand, and strong cross-functional collaboration.
• Consistent contribution to reusable accelerators and internal knowledge base.
• Predictable delivery cadence with strong engineering quality and observability.
• Visible growth of AHEAD's reputation for agentic AI expertise.