6 months ago
Base Salary
$230k - $300k/yr
Responsibilities
- Architect, design, build, and deploy enterprise-grade AI, GenAI, agentic, automation, and ML-enabled solutions.
- Translate business and technical requirements into solution designs, architecture decisions, implementation plans, and engineering workstreams.
- Design RAG, workflow orchestration, agent-assisted process, model integration, API automation, and human-in-the-loop solutions.
- Lead technical workstreams across client engagements, including estimation, planning, development, testing, deployment, risk management, and issue resolution.
- Partner with client engineering, data, cloud, security, and platform teams to integrate AI solutions into enterprise environments.
- Establish engineering standards for testing, CI/CD, observability, monitoring, reliability, scalability, security, maintainability, LLMOps/MLOps, evaluation, guardrails, and responsible AI.
- Lead workshops, architecture sessions, demos, design reviews, and technical discussions with technical and non-technical stakeholders.
- Mentor engineers, consultants, and technical specialists; review technical designs and code.
- Create reusable components, reference architectures, deployment patterns, accelerators, technical methods, and AI offerings.
- Support pre-sales and solution shaping through technical scoping, delivery planning, estimates, risk assessment, and implementation plans.
Requirements
- Typically 7–12+ years of experience in software engineering, ML engineering, applied AI, data science engineering, AI solution architecture, technical consulting, or enterprise technology delivery.
- Strong hands-on engineering experience with Python, APIs, cloud-native development, data integration, workflow automation, and enterprise system integration.
- Experience designing, building, and deploying production-grade AI, GenAI, ML, automation, or advanced analytics solutions.
- Practical familiarity with RAG, LLM application design, agentic workflows, orchestration, model integration, vector databases, evaluation, guardrails, and observability.
- Strong understanding of automated testing, version control, containerization, monitoring, reliability, security, and scalable deployment.
- Ability to lead technical teams, review designs and code, mentor engineers, and drive quality across complex workstreams.
- Strong client-facing communication skills with engineering, executive, and non-technical stakeholders.
- Ability to structure ambiguous technical problems, make architecture decisions, and guide teams toward practical outcomes.
- Preferred experience in applied AI or advanced analytics consulting, ML engineering, AI product development, enterprise AI platforms, cloud and data platforms, LLM frameworks, orchestration tools, vector databases, model serving, ML platforms, AI governance, production transitions, technical pre-sales, solution shaping, or executive technical advisory.
- An advanced degree in computer science, engineering, data science, applied mathematics, or a related field is preferred but not required.
Benefits
- Medical, dental, and vision insurance.
- 401(k).
- Paid company holidays and paid time off.
- Paid parental and caregiver leave.
- Professional development, cross-department training, sponsored certifications, and credentials.
- Additional USA employment benefits are available through AHEAD’s benefits program.
Tech Stack
Categories
Solutions Engineering
About AHEAD
AHEAD is an IT services and consulting firm that designs, builds, and operates digital platforms for large enterprises across cloud infrastructure, automation, data and analytics, security, and DevOps. It generates revenue through consulting, systems integration, and managed services, including cloud management and operations. Founded in 2007 and headquartered in Chicago, it is privately held and owned by Centerbridge Partners.