AI Engineer

Mindlance

Washington, DC

JOB DETAILS
SKILLS
Architectural Services, Artificial Intelligence (AI), Best Practices, Cloud Architecture, Cloud Computing, Communication Skills, Computer Science, Data Science, Design Patterns Programming Methodologies, Diversity, Documentation, Enterprise Architecture, Industry/Trade Analysis, Leadership, Machine Learning, Maintain Compliance, Mentoring, Microsoft Windows Azure, Natural Language Processing (NLP), Private Cloud, Problem Solving Skills, Programming Languages, Public Cloud, Python Programming/Scripting Language, Regulatory Compliance, Search Technology, Security Compliance, Service Delivery, Splunk, Systems Administration/Management, Team Lead/Manager, Technical Leadership, User Interface/Experience (UI/UX), Web Programming
LOCATION
Washington, DC
POSTED
30+ days ago

Title: AI Engineer
Duration: 6 Months Long Term
Location: Washington, DC 20433

Hybrid Onsite: 4 days per week from Day 1, with a full transition to 100% onsite anticipated soon.

Background & Objectives:
The AI Engineer will play a critical role in developing and implementing AI-powered solutions, including generative AI models like ChatGPT and Gemini, to support various initiatives within the client.

Scope of Work:
The AI Engineer will be responsible for designing, developing, and deploying AI solutions that address the needs. This includes working on projects that involve natural language processing, machine learning, generative AI and other AI technologies. The engineer will collaborate with various teams to understand their requirements and deliver AI solutions that improve efficiency, decision-making, and service delivery.

Key Responsibilities

  • Lead the design and implementation of scalable, secure cloud architectures for enterprise solutions leveraging LLM models from Google and OpenAI .
  • Build applications with vector databases and LangChain and understand text embeddings .
  • Develop and maintain cloud-based solutions that integrate LLM models to enhance search capabilities and user experience.
  • Demonstrate experience in Azure technologies, including ASE, Azure Functions, Azure API Management, Azure Service Bus, Logic Apps, Azure Storage, Azure Cognitive Services, Azure Cosmos DB, Azure Data Factory, Databricks, Azure Data Lake, and caching technologies.
  • Provide technical leadership and mentorship to team members, ensuring best practices in cloud architecture and LLM model integration.
  • Ensure compliance with security standards and best practices in cloud architecture and data handling, particularly when dealing with sensitive information processed by LLM models.
  • Address performance and production issues, with extensive knowledge in logging and monitoring using tools such as Splunk and AppInsights.
  • Possess sound technical knowledge and understanding of infrastructure design, including private and public cloud.
  • Establish systems to supervise the operating efficiency of existing application systems and provide proactive maintenance.
  • Participate in systems design, working within an established framework, and provide direction to a team of staff and contractors in their area of expertise.
  • Stay updated with the latest industry trends, cloud technologies, and advancements in LLM models to continually improve enterprise search solutions.
  • Exhibit strong leadership and team-building skills, with the ability to mentor and guide technical teams, and excellent communication skills to articulate complex technical information to non-technical stakeholders.
  • Create detailed architectural documentation and design patterns, and possess knowledge of security standards and compliance requirements in a cloud environment.
Required Qualifications & Experience
  • A degree in Computer Science, Data Science, AI, or a related field.
Technical Skills :
  • Proficiency in programming languages such as Python .
  • Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch).
  • Knowledge of natural language processing and generative AI models.
  • Experience with LangChain, LangGraph and building platform services.
  • Experience in building solutions leveraging Agentic AI .
  • Knowledge and experience with Google Cloud services, Azure technologies, and enterprise search applications .

Professional Experience :
  • At least 3-5 years of experience in AI development and implementation . Over all 6+ years of exp in IT.
  • Experience in prompt engineering and AI governance.
  • Demonstrated experience in cloud-native and hybrid web development projects.
Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.

About the Company

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Mindlance