C
AI Engineer
CACI
2 hours ago
Full-time
On-site
Denver, Colorado, United States
CAСI is hiring an
AI Engineer
to support its AI Center of Excellence, delivering production-ready GenAI applications through short, rotational engagements. The work includes building RAG pipelines, conversational AI platforms, and multi-agent systems, with an emphasis on operationalization, knowledge transfer, and improvement of a reusable solution catalog. Responsibilities
Deliver production-ready AI solutions in
1–2 month
rotations, including
RAG pipelines ,
conversational platforms , and
multi-agent systems , tailored to each program’s mission and technology stack. Build and customize AI solutions using
vector databases ,
orchestration frameworks , and
managed AI services , while implementing
observability ,
security , and
cost controls . Integrate
LLM APIs
and
AI services
into existing workflows, apply
responsible AI guardrails , configure
monitoring/alerting , and troubleshoot integration issues across
cloud and on-prem environments . Lead hands‑on training, create documentation, and pair-program with teams to support independent operation and ongoing evolution of AI applications. Improve existing templates, create reusable patterns, and document new techniques based on field experience. Confirm operational independence through structured handoff and validation processes. Explore emerging GenAI tools, evaluate federal use‑case applicability, and share insights through demos and documentation. Required Qualifications
3–5 years
building production applications with
Python/JavaScript ,
Git workflows , and modern development practices. Practical experience with
LLM-powered apps ,
agent patterns ,
RAG ,
prompt engineering ,
vector databases , and
observability concepts ; hands‑on experimentation preferred. Ability to monitor AI performance ( latency, cost, quality ), address common failure modes, and apply responsible AI practices such as
bias detection
and
guardrails . Strong background designing, implementing, and troubleshooting
RESTful
and
event‑driven
integrations. Experience with
AWS/Azure/GCP ,
containerization ,
CI/CD ,
IaC concepts , and
secure API/key management . Understanding of basic
ML concepts
and how they apply to
LLM systems . Proven ability to deliver solutions quickly in unfamiliar environments with evolving requirements. Strong communication skills, including creating clear documentation and teaching complex AI concepts. Ability to make trade‑offs under pressure, prioritize working solutions, and leverage reusable templates. Active user of modern AI tools, staying current through experimentation and community engagement. Experience with
GitLab ,
Jira , and iterative delivery. Ability to obtain and maintain a
Top Secret
clearance. Preferred Qualifications
Experience deploying
agentic AI systems , using
observability tools ,
vector databases ,
guardrails ,
embeddings , and
structured outputs . AWS (Bedrock/GovCloud),
Azure OpenAI ,
Kubernetes ,
Terraform , and
CI/CD pipeline
experience. Proficiency in
JS/TS/Python
for front‑end/back‑end development and modern frameworks such as
React
or
FastAPI . Experience leading client engagements, context‑switching across projects, and delivering strong knowledge transfer. Familiarity with
DoD/federal missions , security requirements, and compliance frameworks (including
ATO
and
NIST ). History of open‑source work, technical writing, conference speaking, or similar community involvement. Security+ , AWS certifications, or other relevant technical credentials. Technologies
Python, JavaScript, Git LLM-powered apps, LLM APIs, AI services, RAG, prompt engineering Vector databases, embeddings Observability concepts, monitoring/alerting RESTful integrations, event‑driven integrations AWS, Azure, GCP, managed AI services Orchestration frameworks, multi‑agent systems Containerization, CI/CD, IaC Secure API/key management GitLab, Jira Compensation and Location
Location:
Denver, CO (onsite).
Salary range:
USD
82,100
to
172,400
per year. Benefits
Healthcare Wellness Financial Retirement Family support Continuing education Time off benefits Competitive compensation Benefits and learning and development opportunities What You Can Expect
A culture of integrity An environment of trust A focus on continuous growth Flexible time off benefit Access to robust learning resources
#J-18808-Ljbffr
AI Engineer
to support its AI Center of Excellence, delivering production-ready GenAI applications through short, rotational engagements. The work includes building RAG pipelines, conversational AI platforms, and multi-agent systems, with an emphasis on operationalization, knowledge transfer, and improvement of a reusable solution catalog. Responsibilities
Deliver production-ready AI solutions in
1–2 month
rotations, including
RAG pipelines ,
conversational platforms , and
multi-agent systems , tailored to each program’s mission and technology stack. Build and customize AI solutions using
vector databases ,
orchestration frameworks , and
managed AI services , while implementing
observability ,
security , and
cost controls . Integrate
LLM APIs
and
AI services
into existing workflows, apply
responsible AI guardrails , configure
monitoring/alerting , and troubleshoot integration issues across
cloud and on-prem environments . Lead hands‑on training, create documentation, and pair-program with teams to support independent operation and ongoing evolution of AI applications. Improve existing templates, create reusable patterns, and document new techniques based on field experience. Confirm operational independence through structured handoff and validation processes. Explore emerging GenAI tools, evaluate federal use‑case applicability, and share insights through demos and documentation. Required Qualifications
3–5 years
building production applications with
Python/JavaScript ,
Git workflows , and modern development practices. Practical experience with
LLM-powered apps ,
agent patterns ,
RAG ,
prompt engineering ,
vector databases , and
observability concepts ; hands‑on experimentation preferred. Ability to monitor AI performance ( latency, cost, quality ), address common failure modes, and apply responsible AI practices such as
bias detection
and
guardrails . Strong background designing, implementing, and troubleshooting
RESTful
and
event‑driven
integrations. Experience with
AWS/Azure/GCP ,
containerization ,
CI/CD ,
IaC concepts , and
secure API/key management . Understanding of basic
ML concepts
and how they apply to
LLM systems . Proven ability to deliver solutions quickly in unfamiliar environments with evolving requirements. Strong communication skills, including creating clear documentation and teaching complex AI concepts. Ability to make trade‑offs under pressure, prioritize working solutions, and leverage reusable templates. Active user of modern AI tools, staying current through experimentation and community engagement. Experience with
GitLab ,
Jira , and iterative delivery. Ability to obtain and maintain a
Top Secret
clearance. Preferred Qualifications
Experience deploying
agentic AI systems , using
observability tools ,
vector databases ,
guardrails ,
embeddings , and
structured outputs . AWS (Bedrock/GovCloud),
Azure OpenAI ,
Kubernetes ,
Terraform , and
CI/CD pipeline
experience. Proficiency in
JS/TS/Python
for front‑end/back‑end development and modern frameworks such as
React
or
FastAPI . Experience leading client engagements, context‑switching across projects, and delivering strong knowledge transfer. Familiarity with
DoD/federal missions , security requirements, and compliance frameworks (including
ATO
and
NIST ). History of open‑source work, technical writing, conference speaking, or similar community involvement. Security+ , AWS certifications, or other relevant technical credentials. Technologies
Python, JavaScript, Git LLM-powered apps, LLM APIs, AI services, RAG, prompt engineering Vector databases, embeddings Observability concepts, monitoring/alerting RESTful integrations, event‑driven integrations AWS, Azure, GCP, managed AI services Orchestration frameworks, multi‑agent systems Containerization, CI/CD, IaC Secure API/key management GitLab, Jira Compensation and Location
Location:
Denver, CO (onsite).
Salary range:
USD
82,100
to
172,400
per year. Benefits
Healthcare Wellness Financial Retirement Family support Continuing education Time off benefits Competitive compensation Benefits and learning and development opportunities What You Can Expect
A culture of integrity An environment of trust A focus on continuous growth Flexible time off benefit Access to robust learning resources
#J-18808-Ljbffr