AI Engineer

Project overview

Role- AI Engineer

Location- Any sapient office in US (2 days onsite a week)

Visa- GC-EAD, H1-B, -EAD

JD:

Build agentic AI systems: Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access.

Productionize LLMs: Build evaluation framework for open-source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations.

Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.

Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business-aligned outcomes.

Safety, reliability, and governance: Build validator models, adversarial prompts, and policy checks into the stack; enforce deterministic fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk.

Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.

Build a RAG pipeline: Curate domain-knowledge; build data-quality validation framework; establish feedback loops and milestone framework maintain knowledge freshness.

Raise the bar: Drive design reviews, experiment rigor, and high-quality engineering practices; mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns

ESSENTIAL SKILLS

7.

• Boston, MA (Headquarters): 40 Water St, Boston, MA 02109
• :
• : 384 Northyards Boulevard NW, Atlanta, GA 30313
• : 1515 N Courthouse Rd, Arlington, VA 22201
• : 350 Bush St, San Francisco, CA 94104
• : 1111 Bagby St, Houston, TX 77002
• : 205 Hamilton Row, Birmingham, MI 48009
• Denver / Westminster, CO: 11030 Circle Point Rd, Westminster, CO 80020
• Dallas / Irving, TX: 6021 Connection Dr, Irving, TX 75039
• DL front and Back copy is mandatory
• Exp- 10+ years
• For H1-B candidates they must have minimum 3 years of US experience
• Must have valid LinkedIn
• In person interview can be conducted
• 5+ years of software development in one or more languages (Python, C/C++, Go, Java); strong hands-on experience building and maintaining large-scale Python applications preferred.
• 3+ years designing, architecting, testing, and launching production ML systems, including model deployment/serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.
• Practical experience with Large Language Models (LLMs): API integration, prompt engineering, fine-tuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).
• Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
• Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.
• Strong analytical problem-solving, ownership, and urgency; ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.

Nice to have

Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation).

Regards

Ravi Sharma

Job Facts: Contract W2 | Contract Independent | 6 Months | On-site | $60 - $70/hr

Skills: AI, GenAI, Python, java, AWS, Langchain, RAG, LLMs, EC2, S3

Reference: Dice Id: 91163703 | Position Id: 9119302

Project details

• Start: flexible
• Duration: 6 Months
• Remote: onsite
• Location: Dallas, TX, US, US