AI Principal Technical Consultant
New
United StatesFull-TimePrincipal
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 7–12+ years
- Required Skills
- PythonCloud ComputingKubernetesMachine LearningData engineeringMLOpsGenerative AI
Requirements
- 7–12+ years of experience in software engineering, ML engineering, AI architecture, data science engineering, or technical consulting
- Strong hands-on experience with Python, APIs, cloud-native development, and enterprise system integration
- Proven experience designing and deploying production-grade AI, GenAI, or ML-based systems
- Deep familiarity with modern AI patterns such as RAG, LLM orchestration, agentic workflows, vector databases, and model integration
- Strong understanding of cloud and data platforms (AWS, Azure, GCP, Databricks, Snowflake, Kubernetes, or similar)
- Experience with CI/CD pipelines, observability, testing frameworks, security, and scalable deployment practices
- Ability to lead technical teams, review architecture/code, and mentor engineers in complex environments
- Strong communication skills with the ability to translate technical complexity for executives and non-technical stakeholders
- Experience operating in ambiguous, fast-paced consulting or enterprise transformation environments
- Background in applied AI consulting or enterprise AI delivery is highly preferred
Responsibilities
- Design and implement enterprise AI, GenAI, ML, and automation solutions, including RAG, agentic workflows, and orchestration systems
- Translate complex business and technical requirements into scalable architecture designs and implementation roadmaps
- Lead technical delivery across client engagements, including planning, estimation, execution, risk management, and deployment
- Act as the primary technical authority, ensuring engineering quality, scalability, security, and reliability of AI systems
- Partner with client engineering, cloud, data, and security teams to integrate AI solutions into enterprise environments
- Facilitate technical workshops, architecture reviews, and executive-level discussions with both technical and non-technical stakeholders
- Define and enforce production-grade engineering standards including CI/CD, testing, observability, and LLMOps/MLOps practices
- Build reusable frameworks, accelerators, and reference architectures to strengthen enterprise AI delivery capabilities
- Support pre-sales and solution shaping activities, including scoping, technical design, and effort estimation
- Mentor engineers and consultants to elevate delivery quality and strengthen internal AI capabilities
View Full Description & ApplyYou'll be redirected to the employer's site
