Spark Tek Inc
Posted 142 days agoVerified live 2d ago
AI Engineer
Brief overview
Owings MIlls, MDIn-person
2+ yrsMinimum
29 H-1B approvalsDept. of Labor
1 green cardsCertified filings
PythonTypeScriptLangChainAutoGenSemantic Kernelprompt engineeringRAG (retrieval-augmented generation)vector databasesPineconeFAISSWeaviateLLM APIsOpenAI GPT-4ClaudeLLaMAMistralcloud-native development
About the company
Spark Tek Incsparktekusa.com
Spark Tek Inc offers IT solutions and consultancy services, specializing in IT services and consulting for various industries.
Visa sponsorship history
4 years sponsoring, last filed FY2026
Data powered by U.S. Department of Labor. This does not guarantee sponsorship for this specific role.29H-1B approved
94%approval rate
18new H-1B hires
1PERM certified
$126,880median wage / yr
H-1B Petition ApprovalsVisas USCIS actually granted: the strongest sign the company sponsors.
20237
202412
20257
20263
LCA Certified ApplicationsAn early filing step, not a visa approval: it signals intent, not confirmed sponsorship.
20241
20252
20261
Green Card (PERM) FilingsCertified green card filings: a long-term commitment to international hires.
20261
Top sponsored roles
SR. DEVOPS ENGINEERLEAD SOFTWARE DEVELOPERSOFTWARE ENGINEER
Job description
Summary
Spark Tek Inc is seeking an AI Engineer to design and develop advanced agentic systems and enterprise-grade applications powered by LLMs and multimodal models. This hands-on DevOps role involves significant influence over architectural decisions and collaboration with product leads, data scientists, and platform engineers to deliver scalable AI Ops solutions.
Responsibilities
- Design and develop autonomous AI agents and multi-step workflows that utilize LLMs, tool use, and memory/context chaining
- Build custom accelerators to automate knowledge tasks (e.g., analytics generation, support automation, code generation)
- Fine-tune or adapt foundation models (e.g., OpenAI, Claude, Mistral, LLaMA) for targeted use cases
- Integrate agentic capabilities with APIs, vector stores, databases, and third-party tools using orchestration frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.)
- Define architecture, data flows, and security protocols for scalable GenAI applications
- Partner with stakeholders to identify high-value AI opportunities and quickly prototype viable solutions
- Stay current on LLM research and industry trends; advise on model and framework selection
Skills
- 2+ years in DevOps experience with familiarity to AI/ML systems; AI or LLM-based application development / DevOps experience preferred
- Strong experience with Python (preferred), TypeScript, or similar languages
- Proven experience building agentic systems using LangChain, AutoGen, Semantic Kernel, or custom orchestration
- Experience with prompt engineering, RAG (retrieval-augmented generation), and vector databases (e.g., Pinecone, FAISS, Weaviate)
- Deep understanding of LLM APIs and models (e.g., OpenAI GPT-4, Claude, LLaMA, Mistral)
- Familiarity with cloud-native development (AWS), containers, and CI/CD pipelines
- Strong product thinking, with the ability to translate user needs into impactful AI solutions
- Experience with multi-agent systems, tool-use chaining, and long-term memory persistence
- Exposure to MLOps practices and model deployment pipelines
- Knowledge of privacy, security, and compliance in AI applications
Qualifications
Must Haves
- 2+ years in DevOps experience with familiarity to AI/ML systems; AI or LLM-based application development / DevOps experience preferred
- Strong experience with Python (preferred), TypeScript, or similar languages
- Proven experience building agentic systems using LangChain, AutoGen, Semantic Kernel, or custom orchestration
- Experience with prompt engineering, RAG (retrieval-augmented generation), and vector databases (e.g., Pinecone, FAISS, Weaviate)
- Deep understanding of LLM APIs and models (e.g., OpenAI GPT-4, Claude, LLaMA, Mistral)
- Familiarity with cloud-native development (AWS), containers, and CI/CD pipelines
- Strong product thinking, with the ability to translate user needs into impactful AI solutions
Nice to Haves
- Experience with multi-agent systems, tool-use chaining, and long-term memory persistence
- Exposure to MLOps practices and model deployment pipelines
- Knowledge of privacy, security, and compliance in AI applications
