The Role
The Senior AI Engineer will develop and deploy multi-agent systems, automate workflows, integrate enterprise systems, and mentor junior engineers while ensuring quality and security compliance.
Summary Generated by Built In
AHEAD builds platforms for digital business. By weaving together advances in cloud infrastructure, automation and analytics, and software delivery, we help enterprises deliver on the promise of digital transformation.
At AHEAD, we prioritize creating a culture of belonging, where all perspectives and voices are represented, valued, respected, and heard. We create spaces to empower everyone to speak up, make change, and drive the culture at AHEAD.
We are an equal opportunity employer, and do not discriminate based on an individual's race, national origin, color, gender, gender identity, gender expression, sexual orientation, religion, age, disability, marital status, or any other protected characteristic under applicable law, whether actual or perceived.
We embrace all candidates that will contribute to the diversification and enrichment of ideas and perspectives at AHEAD.
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.
The compensation range indicated in this posting reflects the On-Target Earnings (“OTE”) for this role, which includes a base salary and any applicable target bonus amount. This OTE range may vary based on the candidate’s relevant experience, qualifications, and geographic location.
Why AHEAD:
Through our daily work and internal groups like Moving Women AHEAD and RISE AHEAD, we value and benefit from diversity of people, ideas, experience, and everything in between.
We fuel growth by stacking our office with top-notch technologies in a multi-million-dollar lab, by encouraging cross department training and development, sponsoring certifications and credentials for continued learning.
USA Employment Benefits include:
- Medical, Dental, and Vision Insurance
- 401(k)
- Paid company holidays
- Paid time off
- Paid parental and caregiver leave
- Plus more! See benefits https://www.aheadbenefits.com/ for additional details.
Use of AI:
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, assessing responses, or to capture recordings and create transcriptions or summaries during interviews. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please refer to the Candidate Privacy Notice or contact us at [email protected].
You may opt-out of the review or analysis of your application and resume by AI tools by using the General Application. Please include the role you wish to apply for in the Additional Information field. You may also choose to opt-out of recording and transcription at any time, including after joining an interview. Candidates will not be penalized for choosing to opt-out.
Skills 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.
- 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.
AHEAD Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about AHEAD and has not been reviewed or approved by AHEAD.
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Retirement Support — 401(k) contributions are matched dollar-for-dollar on the first $5,000 each year, with matching made each pay period and immediate 100% vesting. This structure signals above-standard employer support for retirement savings.
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Affordable Benefits — Medical options include low employee premiums for PPO and HDHP plans, and the HDHP adds employer HSA funding plus a dollar-for-dollar HSA match up to stated amounts. Dental and vision plans list very low per-paycheck costs, helping keep overall healthcare spend manageable.
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Wellbeing & Lifestyle Benefits — No-cost telemedicine (including virtual mental health when enrolled), free Calm access for the employee and dependents, and an EAP with counseling are included. Company-paid life and disability plus voluntary protections (legal/ID, pet insurance) and other extras round out a comprehensive set of supports.
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The Company
What We Do
AHEAD builds platforms for digital business. By weaving together cloud infrastructure, intelligent operations, and modern applications, we help enterprises deliver on the promise of digital transformation.
