5G RAN L1/L2 Protocol Developer- Tieto Tech Consulting (m/f/d)
Tietoevry is hiring a 5G RAN L1/L2 Protocol Developer- Tieto Tech Consulting (m/f/d) in Bengaluru, India. Level rates it ; you can apply on Tietoevry.
Level's read on this job
- Level rates this role Little AI ●○○○: aI is not part of the work.
- Level classes it as a senior role.
- Tietoevry has 397 other open roles on Level.
AI in this role
Job Title:5G RAN L1/ L2 Developer
Location: Bengaluru
Experience:
6 to 10 Years experience in Wireless Telecommunications or Networking background having hands on experience in LTE/5G NR L1/L2 protocol software development.
Education:
B. E/ B. S/ B. Tech/ M.S/ME/MTech in EC/EE/CS or any other equivalent degree.
Responsibilities:
Job Description:
As a Software developer, you will be responsible for driving the development and testing of various nodes of 5G NR protocol software. You will develop high technology solutions within the radio access network of the 5G mobile communication system. You will work closely with our customers and your colleagues in agile Scrum teams worldwide to develop and improve solutions for the future.
- You will be contributing to product development, LLD, features development and verification of gNodeB.
- Actively work with client and cross team to carry out system integration and testing.
- Focus to continuously improve system performance with quality deliverables.
- Work closely with other domain specialists.
- Document development processes and test outcomes comprehensively.
Mandatory Skills:
- Candidate should have hands-on experience in LTE/5G NR Mac Scheduler, 3GPP Layer1/Layer 2.
- Candidate should possess in-depth knowledge of 3GPP Specification - specifically Layer 1/L2
- Understanding of Layer1 - Layer2 interfaces and Layer2 - Layer3 interfaces
- Candidate must have knowledge of networking protocols like TCP/IP, UDP, SCTP etc.
- Must have experience in debugging complex gNodeB issues, log file analysis etc.
- Proficient Agile development methodologies.
- Candidate should have good coding skills in C /C++
- Programming skills: C++ (target), Java and Python (testers), VsCode, Git, Gerrit
- Build systems: Bazel
- Cloud Basics: Understanding key cloud concepts, including containers, Docker, Kubernetes, and cloud-native architectures, is crucial.
- Domain Knowledge: Specific knowledge around CloudRAN implementations, such as virtualized Distributed Units (vDU), RAN technologies, and connectivity protocols, is required.
- Proficient in using version control tools such as Git, Gerrit, and project management tools like Jira.
- The candidate should have experience of agile ways of working.
- Experience from cloud technologies like microservices, containers, etc. is also a merit.
- Candidate should have excellent communication skills and enjoy working in a dynamic and global environment.
At Tieto, we believe in the power of diversity, equity, and inclusion. We encourage applicants of all backgrounds, genders (m/f/d), and walks of life to join our team, as we believe that this fosters an inspiring workplace and fuels innovation. Our commitment to openness, trust, and diversity is at the heart of our mission to create digital futures that benefit businesses, societies, and humanity.
Diversity, equity and inclusion | Sustainability | Tieto
Stay alert to recruitment scams:
• Tieto only communicates via @tieto.com email addresses.
• We never ask candidates to pay fees or share financial details during recruitment.
• If you receive a suspicious message claiming to be from Tieto, don't respond — verify it via our official careers site.
• For more information visit Important Advisory Regarding Recruitment Fraud | Tieto Blog
How we rate this
5G RAN L1/L2 Protocol Developer- Tieto Tech Consulting (m/f/d) at Tietoevry rates 30 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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