AI/ML Backend Developer
Job in
Washington, District of Columbia, 20560, USA
Listed on 2026-09-25
Listing for:
SRI Tech
Full Time
position Listed on 2026-09-25
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer, Python, Data Scientist
Job Description & How to Apply Below
Location:
DC, WA
Employment Type:
C2C, Full Time Client:
TechMContact:
Meghana Gorusu Company: SRI Tech Solutions
Job Title:
AI/ML Backend Developer
Location:
Washington DC (Onsite)
Contract / Fulltime
Job Summary The ideal candidate should have a solid background in backend development, AI/ML orchestration, and data management, with hands-on experience in Generative AI and Agentic Al frameworks. They will be responsible for building REST APIS, managing data pipelines, and implementing AI/ML solutions such as retrieval-augmented generation (RAG), intent detection models, and autonomous AI agents to deliver intelligent, production-ready solutions.
Key Responsibilities:
Backend Development:
Design, develop, and maintain REST APIs using Python to integrate AI/ML services.
Agentic AI Development:
Design and orchestrate AI agents capable of reasoning, planning, and executing multi-step tasks by integrating LLMs with APIs, tools, and data sources.
AI/ML Orchestration:
Implement and manage machine learning models, large language models (LLMs), Agentic AI workflows and AI orchestration using Python.
Generative AI Solutions:
Using Generative Al models for tasks like text generation, summarization, conversational Al, and content creation.
Data Management:
Work with structured databases (SQL), graph databases (e.g., CosmosDB), and unstructured data stores (e.g., Elasticsearch).RAG Implementation:
Build retrieval-augmented generation (RAG) pipelines leveraging Azure AI Search, ANS Open Search, or other vector databases for contextual responses.
Data Pipelines:
Design and manage robust data ingestion and transformation pipelines to feed Al models.
Intent Detection & NLU:
Develop or integrate intent detection models and natural language understanding (NLU) solutions to enhance conversational AI. Prompt Engineering & Optimization:
Create and optimize prompts for LLMs to improve response quality and reduce latency,AI Integration:
Collaborate with frontend and product teams to embed Gen Al features into enterprise applications
Required Skills:
Backend Development:
Proficient in Python for building and maintaining scalable REST APIS, familiarity with integrating Al services.
AI/ML Orchestration:
Strong expertise in Python with a focus on machine learning, large language models (LLMs), AI orchestration.
Agentic AI Expertise:
Experience in building autonomous AI agents using frameworks like OpenAI Functions, or custom orchestration solutions to handle tool use and multi-step reasoning.
Generative AI Expertise:
Generative Al models (text generation, summarization, conversational AI) and applying prompt engineering techniques.
Data Management:
Solid understanding of structured (SQL), graph (CosmosDB), and unstructured (Elasticsearch) databases; ability to design efficient data access patterns for AI workloads.
RAG Implementation:
Proven experience implementing retrieval-augmented generation using Azure AI Search, AWS Open Search, or other vector databases.
Data Pipelines:
Hands-on experience building and managing data ingestion and transformation pipelines using Databricks,Azure Data Factory, or equivalent tools. Intent Detection & NLU:
Skilled in developing or deploying intent detection models and natural language understanding (NLU) components for conversational AI applications.
Preferred
Skills:
Familiarity with cloud platforms such as Azure and AWS.Knowledge of additional AI/ML frameworks and tools.
Knowledge of Agentic AI Experience with Dev Ops practices and CI/CD pipelines.
SRI Tech Solutions is an equal opportunity employer and does not discriminate on the basis of race, color, gender, religion, age, sexual orientation, national origin or citizenship status or ethnic origin, disability, marital status, veteran status, or any other occupationally irrelevant criteria.
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