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Calling Agents Jobs (NOW HIRING)

eClercx

Senior AI Engineer

Manhattan, NY · On-site

$100K - $120K/yr

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol.

eClerx

Senior AI Engineer

Dallas, TX · On-site

$105K - $150K/yr

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol.

eClercx

Senior AI Engineer

Dallas, TX · On-site

$105K - $150K/yr

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol.

eClercx

Senior AI Engineer

New York, NY · On-site

$180K - $200K/yr

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol.

Numeral, Inc.

Software Engineer (AI)

New York, NY · On-site

$175K - $300K/yr

Design, build, and operate production AI systems, including tool-calling agents, model orchestration layers, and RAG. * Implement and maintain AI integrations using modern frameworks, MCP servers ...

eClerx

Senior AI Engineer

Manhattan, NY · On-site

$100K - $120K/yr

Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol.

NMK Global Inc.

Sr. Applied AI Engineer

Mountain View, CA · On-site

$143K - $189K/yr

... agents, multi-step task orchestration, tool-calling loops, and human-in-the-loop interaction patterns • Own agentic features end to end -- from architecture and implementation through testing ...

Arka Innovate

Tool/API calling agents * Background processing workflows * Job runners and schedulers Strong experience in data modeling and schema design , including: * Use of type‑safe models (e.g., Pydantic or ...

NTT DATA, Inc.

Agentic AI Engineer

Los Angeles, CA · On-site

BuildLLM-powered systems(RAG, tool-calling agents, multi-agent orchestration) * Develop classical ML models (risk scoring, prediction, clustering, anomaly detection) * ImplementHIPAA aware AI ...

Xclusive Homes, LLC

Office Assistant

Naples, FL

$35K/yr

Respond to emails and print documents as needed for agents. * Assist in calling agents and requesting documentation when necessary. Administrative Assistance: * Scan mail and forward checks and ...

Delinea

LLM inference, retrieval, tool calling, agents, and evaluation. You will own a portion of the Iris AI roadmap and the engineers delivering it, hold a high bar for how LLM-powered features are built ...

Newcode.ai

Senior FastAPI Developer

$55.75 - $73.75/hr

RAG, tool-calling, agents. You know where they tend to break. * You use AI coding tools (Claude Code, Cursor, Copilot) and use them well. Faster output, but you understand and stand behind every line ...

Gravity IT Resources

Application Security Engineer

Miami, FL · On-site

$56.25 - $75/hr

This is not a traditional AppSec role -- the ideal candidate is comfortable securing non-deterministic systems, tool-calling agents, and identity-driven control planes, while applying proven web, API ...

New

Cerebras

Staff Research Engineer

California, MO · On-site

MCP-based Environments for general function-calling agents across various enterprise and consumer applications The Staff Research Engineer - Code will own end-to-end the creation of datasets, RL ...

Turing

Senior Research Engineer

Palo Alto, CA · On-site

$122K - $168K/yr

MCP-based Environments for general function-calling agents across various enterprise and consumer applications The Senior Research Engineer will own end-to-end the creation of datasets, RL ...

Mainspring Energy

Senior DevOps Engineer

Menlo Park, CA

$134K - $158K/yr

Strong software engineering fundamentals in Python, paired with practical experience leveraging AI, LLM tooling, or agentic frameworks (e.g., Google ADK, LangChain, or custom tool-calling agents) for ...

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Senior AI Engineer

Manhattan, NY • On-site

eClercx
See more jobs at eClercxexternal

$100K - $120K/yr

Full-time

Re-posted 12 days ago

Job description

Responsibilities
Senior AI Engineer
Location: Salt Lake City, Utah
Type: Full-time
Department: BFSI
Job Summary
In this role, you will be responsible for launching and implementing GenAI agentic solutions aimed at reducing the risk and cost of managing large-scale production environments with varying complexities. You will address various production runtime challenges by developing agentic AI solutions that can diagnose, reason, and take actions in production environments to improve productivity and address issues related to production support.
Responsibilities
  • 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

Eligibility Requirements
  • 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.
  • Preferred: 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).

In the US, the target base salary for this role is $100K-$120K. Compensation is based on a range of factors that include relevant experience, knowledge, skills, other job-related qualifications, and geography. We expect the majority of candidates who are offered roles at our company to fall throughout the range based on these factors
How to Apply
  • Click "Apply Now" to submit your resume through our career site
  • Be sure to include any relevant experience that aligns with the role.
  • Qualified candidates will be contacted by a member of our recruitment team for next steps

About eClerx
eClerx is a leading provider of productized services, bringing together people, technology and domain expertise to amplify business results.
The firm provides business process management, automation, and analytics services to a number of Fortune 2000 enterprises, including some of the world's leading financial services, communications, retail, fashion, media & entertainment, manufacturing, travel & leisure, and technology companies. Incorporated in 2000, eClerx is traded on both the Bombay and National Stock Exchanges of India. The firm employs more than 19,000 people across Australia, Canada, France, Germany, Switzerland, Egypt. India, Italy, Netherlands, Peru, Philippines, Singapore, Thailand, the UK, and the USA.
For more information, visit www.eclerx.com
You can also find us on:
https://www.linkedin.com/company/eclerx/
https://www.indeed.com/cmp/Eclerx/about
https://www.glassdoor.com/eClerx
eClerx is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law. We are also committed to protecting and safeguarding your personal data. Please find our policy here

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