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Day Shift Java C2C Jobs in Austin, TX (NOW HIRING)

Acrisure, LLC

Software Engineer, Data (L1)

Austin, TX · On-site

$113K - $136K/yr

Austin, TX (Onsite 4 days per week)*****Note: This is a full-time role and we do not offer C2C or ... Proficient in Scala, Python, or Java* Well versed in Data Lake & Delta Lake Concepts* Understanding ...

Acrisure

Software Engineer, Data (L1)

Austin, TX · On-site

$113K - $136K/yr

... TX (Onsite 4 days per week) Note: This is a full-time role and we do not offer C2C or C2H ... Proficient in Scala, Python, or Java * Well versed in Data Lake & Delta Lake Concepts

Acrisure

Senior Software Engineer

Austin, TX · On-site

$121K - $160K/yr

Four Days in Office) Note: This is a full-time role and we do not offer C2C or C2H employment and ... We code primarily in Kotlin, Python, Java, and JavaScript and make use of many frameworks ...

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Day Shift Java C2C information

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$15

$56

$76

How much do day shift java c2c jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for day shift java c2c in Austin, TX is $56.20, according to ZipRecruiter salary data. Most workers in this role earn between $48.61 and $62.88 per hour, depending on experience, location, and employer.

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Day Shift Java C2C jobs near you
Infographic showing various Day Shift Java C2C job openings in Austin, TX as of August 2026, with employment types broken down into 1% As Needed, 67% Full Time, 27% Part Time, and 5% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $116,895 per year, or $56.2 per hour.

Agentic AI Architect (Only local to TX)- C2C Requirements

Austin, TX • On-site

Tech Mirrors
See more jobs at Tech Mirrorsexternal

$70/hr

Other

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

Austin, TX (Hybrid – 3 days/week)

6 months (Possible extension)

Rate: $70/hr c2c (Max)

Note: Please ensure that candidates complete the home exercise. Kindly communicate this requirement to the candidates in advance.

Principal Architect with Deep AI & Agentic Systems – Detailed JD

Principal Architect with deep AI and agentic systems expertise to design and deliver production-grade, server-hosted AI solutions. This role requires a balance of architecture leadership and hands‑on engineering, with a strong focus on LLM orchestration, memory management, advanced retrieval (RAG), and enterprise-grade agent workflows.

The ideal candidate has proven experience building scalable agentic systems in enterprise environments, not just experimental or IDE-based solutions, and can design systems that integrate business context, code intelligence, and human-in-the-loop workflows.

Must-Have Skills

Recruiters should screen strongly for the following:

1) Agentic AI / LLM Systems
  • Proven experience building agentic systems that run-in server environments
  • Experience with multi-step orchestration, tool calling, and workflow design
  • Hands‑on implementation experience — not just conceptual AI knowledge
2) Memory and Context Management
  • Experience designing short-term and long-term memory for AI systems
  • Understanding of how to manage context across sessions, tasks, and workflows
  • Familiarity with state handling, summarization, persistence, and context optimization
3) Advanced Retrieval / RAG

Strong experience with advanced RAG architectures

Hands‑on work with:

  • Vector databases
  • Graph databases
  • Embeddings and retrieval design
  • Experience with hybrid retrieval patterns and building richer context for AI systems
4) Code Intelligence / Technical Analysis
  • Experience ingesting source code and documents into AI/retrieval workflows
  • Ability to support: impact analysis, dependency mapping, technical analysis, code relationship/call graph understanding
  • Experience with AST parsing using tools such as Tree-sitter or similar
5) Programming / Engineering Depth

Strong hands‑on experience in:

  • Python or Java
  • Agentic Platforms, RAG/GraphDB, LLMs
  • Caching – near and distributed (Redis ,Apache Ignite etc)
  • API Token management optimization techniques is a plus
  • Experience with SOLR, Lucene or equivalent is a plus
  • AWS Cloud Experience is a plus

Enough engineering depth to contribute meaningfully to implementation and technical design

6) Frameworks / Platforms

Experience with one or more of the following is important:

  • LangGraph
  • LangChain
  • GitHub Copilot SDK or similar
  • CLI-based/server-hosted execution models
  • Managed cloud AI platforms such as Bedrock or similar offerings
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