AI Engineer
Maneva
AWSAzureCloudDockerGoogle Cloud PlatformIoTKerasLinuxPythonPyTorchScikit-LearnTensorflow
Salary
💰 $55,250 - $99,875 per year
Job Level
JuniorMid-Level
Tech Stack
AzureCloudDockerGoogle Cloud PlatformKubernetesLinuxOpen SourcePythonPyTorchSDLCTensorflowVMware
About the role
- Collaborate with Agentic AI Scientists to build and deploy AI agents to automate and optimize workflows and empower the human workforce
- Perform both R&D and customer-facing work to transition applied research into operational impact
- Write software code to support AI agent communication and connect models/agents to external services via API calls
- Support testing, debugging, deployment into target environments, set up monitoring, and ensure reliable execution of agentic AI systems
- Utilize a combination of open source models, agentic tools, and large proprietary commercial models
- Develop novel approaches to securing agentic workflows and evaluate results for accuracy, performance, and impact
- Ensure AI systems adhere to ethical guidelines, transparency, and fairness principles
- Conduct research, develop prototypes, evaluate and document results, and present findings at conferences or public forums
- Integrate solutions into operational environments or mission systems as part of a team
Requirements
- Practical understanding of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen
- Ability to design and implement tool-using AI agents, including API integration, retrieval-augmented generation (RAG), and memory/context management
- Experience employing vector databases (Pinecone, Weaviate, FAISS)
- Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)
- Self-starter with a high degree of intellectual curiosity
- Proficiency in modern software language such as Python
- Ability to obtain a Secret clearance
- Bachelor's degree in Computer Science, Engineering or related field (T1)
- T2: Bachelor's degree and 2+ years of relevant experience, or a Master's degree with relevant experience
- Preferred: hands-on experience with generative AI models, prompt engineering, chain-of-thought reasoning, and NLP tasks
- Preferred: Experience with the Software Development Lifecycle (SDLC), including DevSecOps practices
- Preferred: Hands-on experience with AI service integration such as NIMS, Azure OpenAI, Bedrock, GCP Vertex AI
- Preferred: Proficiency in scripting with Linux Bash, PowerShell, or equivalent automation tools
- Preferred: Hands-on GPU programming experience for ML workloads using CUDA, PyTorch, or TensorFlow
- Preferred: Expertise in designing and implementing safety, guardrails, and bias-mitigation strategies for autonomous agents and multi-agent systems
- Preferred: Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration, and coordination at scale
- Preferred: Familiarity with evaluation and observability tools for AI agents, such as LangSmith, OpenAI Evals, or custom telemetry systems
- Preferred: Experience integrating agents with cloud-native workflows, streaming data pipelines, and real-time decision-making environments
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