GenAI Solution Architect -

Job Title:
GenAI Solution Architect

Location: Denver, CO (3 days onsite/week)

Rate:

NOTE: Experience in Cognigy will be a huge
plus

Scope of work

We are seeking a GenAI Solution Architect to lead the design
and implementation of scalable, secure, and responsible AI/ML solutions. In
this role, youll bridge business needs with technical execution, architecting
backend systems, enabling agentic RAG, and ensuring AI adoption is both
innovative and compliant. Youll work across teams to design cloud-native AI
architectures, optimize costs, and embed observability and responsible AI
practices into every solution.



Key Responsibilities

• Design and implement
  backend architectures for scalable GenAI solutions.


• Build agentic RAG pipelines
  with strong context management.


• Lead model grounding,
  fine-tuning, and distillation for enterprise AI.


• Implement observability and
  monitoring frameworks for AI in production.


• Drive responsible AI
  practices, aligning with risk and compliance policies.


• Integrate GenAI frameworks,
  cloud services, and container orchestration.


• Optimize AI deployments for
  scalability, resilience, and cost efficiency.


• Lead agile project
  delivery, mentoring technical teams.


• Communicate architectural
  decisions clearly to both technical and business leaders.

Required Qualifications

• 15%2B years of experience in
  building and scaling software systems.


• Proven expertise in backend
  and distributed cloud-native architectures.


• Hands-on experience with
  Generative AI techniques: agentic RAG, prompt context, grounding,
  fine-tuning.


• Strong knowledge of
  responsible AI, risk, and compliance frameworks.


• Proficiency in
  containerization (Docker) and orchestration (Kubernetes).


• Experience with Cognigy.AI
  or similar conversational AI platforms.


• Skilled in cloud platforms
  (AWS, Azure, Google Cloud Platform) for AI deployments.


• Familiarity with GenAI
  frameworks (e.g., LangChain, LlamaIndex, Haystack).


• Experience with MLOps,
  CI/CD, and AI observability.


• Excellent communication and
  leadership skills with experience in agile delivery.


• Strategic thinker with
  strong problem-solving and analytical abilities.

Preferred Qualifications

• Experience with model
  distillation and cost optimization.


• Background in multi-cloud
  or hybrid AI deployments.


• Knowledge of vector
  databases, retrieval pipelines, and embeddings.


• Certifications in AI/ML,
  cloud architecture, or responsible AI.